Publications

by the Process Control & Informatics Unit

I. Book chapters

II. Refereed Journal Publications

III. Conference Proceedings Publications

IV. Conference Presentations

V. Conference Presentations in Greece

VI. Technical Reports

 

I. Book chapters

I.1 E. Aggelogiannaki, H. Sarimveis. “Model Predictive Control for distributed parameter Systems using RBF Neural Networks”, in “Informatics in Control, Automation and Robotics II”, Eds. J. Filipe, J.L. Ferrier, J. A. Cetto, M. Carvalho, Springer, 2007.

I.2 P.L. Zervas, A. Tatsis, H. Sarimveis, M.K. Koukou, N.C. Markatos. “CFD Modeling and Optimization of Fuel-Cell Systems“, in “Progress in Fuel Cell Research”, Ed. Petr V. Alermo, Nova Science Publishers, 2007.

Ι.3 Ph. Doganis, H. Sarimveis, “Mixed Integer Linear Programming Scheduling in the Food Industry”, in “Optimization in Food Engineering”, Ed. F. Erdogdu, Taylor and Francis/CRC, 2009.

 

II. Refereed Journal Publications

II.1 Sarimveis, H., H. Genceli and M. Nikolaou. Rigorous design of robust Model Predictive Controllers for processes with more inputs than outputs. (Computers & Chemical Engineering, 20, 972, S1065-S1070, 1996).

II.2 Sarimveis, H., H. Genceli and M. Nikolaou, Design of robust non-square constrained Model Predictive Control. (AIChE Journal, 42, 9, 2582 – 2593, 1996).

II.3 Sarimveis H., “Training algorithms and learning abilities of three different types of neural networks”, (Systems Analysis Modeling Simulation, 38, 555-581, 2000).

II.4 Sarimveis, H. and Th. Retsina, “Tissue softness prediction using neural network methodologies”, (Pulp&Paper Canada, 102, 42-45, 2001).

II.5 Sarimveis, H., “Inferential neural network sensors for on-line prediction of tissue paper quality parameters”, (Chemical Engineering Communications, 188, 231-242, 2001).

II.6 Tsekouras, G, H. Sarimveis and G. Bafas, “A method for fuzzy system identification based on clustering analysis”, (Systems Analysis Modeling Simulation, 39,543-558, 2002).

II.7 Tsekouras, G, H. Sarimveis, C. Raptis and G. Bafas, “A fuzzy logic approach for system qualitative characteristics”, (Computers & Chemical Engineering, 26, 429-438, 2002).

II.8 Sarimveis, H., A. Alexandridis, G. Tsekouras and G. Bafas, “A fast and efficient algorithm for  training radial basis function neural networks based on a fuzzy partition of the input space”, (Industrial & Engineering Chemistry Research, 41, 751-759, 2002).

II.9 Alexandridis, A., Κ. Siettos, H. Sarimveis, A. Boudouvis and G. Bafas, “Modeling of  nonlinear process dynamics using Kohonen’s neural networks, fuzzy systems and Chebyshev series”, (Computers & Chemical Engineering, 26(4-5), 479-486, 2002).

II.10 Korres, D, G. Anastopoulos, E. Lois, A. Alexandridis, H. Sarimveis, G. Bafas, “A neural network    approach to the prediction of diesel fuel lubricity”, (Fuel, 81(10), 1243-1250, 2002).

II.11 Sarimveis, H., A. Angelou, Th. Retsina, G. Bafas, “Minimization of production cost through optimal selection of inventory levels and production rates in pulp and paper mills” (TAPPI Journal, 2(7) 13-18, 2003).

II.12 Sarimveis,H., A. Angelou, Th. Retsina, S. Rutherford, G. Bafas, “Optimal energy management in      pulp and paper mills”, (Energy Conversion and Management, 44(10) 1707-1718, 2003).

II.13 Sarimveis,H., G. Bafas, “Fuzzy model predictive control of nonlinear processes using genetic algorithms”, (Fuzzy Sets and Systems, 139(1) 59-80, 2003).

II. 14 Alexandridis, A., H. Sarimveis, G. Bafas, “A new algorithm for online structure and parameter adaptation of RBF networks”, (Neural Networks, 16(7) 1003-1017, 2003).

II.15 Tsekouras, G., H. Sarimveis, G. Bafas, “A simple algorithm for training fuzzy systems using input-output data” (Advances in Engineering Software, 34(5) 247-259, 2003).

II.16 Sarimveis, H, A. Alexandridis, G. Bafas, “A fast training algorithm for RBF networks based on subtractive clustering” (Neurocomputing, 51 501-505, 2003).

II.17 Karonis D., E. Lois, S. Stournas, F. Zannikos, A. Alexandridis, H. Sarimveis, “A neural network approach for the correlation of exhaust emissions form a diesel engine with diesel fuel properties”, (Energy and Fuels, 17(5), 1259-1265, 2003).

II.18 Sarimveis H. A. Alexandridis, S. Mazarakis, G. Bafas, “A new algorithm for developing dynamic radial basis function neural network models based on genetic algorithms”, (Computers and Chemical Engineering, 28(1-2), 209-217, 2004).

II.19 Vakalis, D., H. Sarimveis, C. T. Kiranoudis, A. Alexandridis, G. Bafas, “A GIS based operational system for wildland fire crisis management. I. Mathematical modeling and simulation”, (Applied Mathematical Modelling, 28(4), 389-410, 2004).

II.20 Vakalis, D., H. Sarimveis, C. T. Kiranoudis, A. Alexandridis, G. Bafas, “A GIS based operational system for wildland fire crisis management. II. System architecture and case studies”, (Applied Mathematical Modelling, 28(4), 411-425, 2004).

II.21 Keramitsoglou, I., C. Kiranoudis, H. Sarimveis, N. Sifakis, “A Multidisciplinary decision support system for forest fire crisis management”, (Environmental Management, 33(2),  212-225, 2004).

II.22 Tsekouras G., H. Sarimveis, “A new approach for measuring the validity of the fuzzy c-means algorithm”, (Advances in Engineering Software, 35(8-9), 567-575, 2004).

II.23 Alexandridis, A., H. Sarimveis, G. Bafas, “Modeling and control of continuous digesters using the PLS methodology”, (Chemical Engineering Communications, 191(10), 1271-1284, 2004).

II.24 Sarimveis H. and A. Nikolakopoulos, “A line up evolutionary algorithm for solving nonlinear constrained optimization problems”, (Computers and Operations Research, 32(6), 1599-1514, 2005).

II.25 Tsekouras G., H. Sarimveis, E. Kavakli, G. Bafas  “A hierarchical fuzzy-clustering approach to fuzzy modeling”,  (Fuzzy Sets and Systems, 150(2), 245-266, 2005).

II.26 Alexandridis A., P. Patrinos, H. Sarimveis, G. Tsekouras, “A two-stage evolutionary algorithm for variable selection in the development of RBF neural network models”, (Chemometrics and Intelligent Laboratory Systems, 75(2), 149-162, 2005).

IΙ. 27 Afantitis Α., G. Melagraki, K. Makridima, A. Alexandridis, H. Sarimveis, O. Iglessi-Markopoulou, “Prediction of High Weight Polymers Glass Transition Temperature Using RBF Neural Networks” (ΤΗΕOCHEM: Journal of Molecular Structure, 716(1-3), 193-198, 2005).

II.28 Keramitsoglou I., H. Sarimveis, C. T. Kiranoudis, N. Sifakis, “Radial basis function neural networks classification using very high spatial resolution satellite imagery: An application to the habitat area of Lake Kerkini (Greece)” (International Journal of Remote Sensing, 26(9), 1861-1880, 2005)

II.29 Doganis, Ph., H. Sarimveis, D. Koufos, G. Bafas, “An MILP model for optimal scheduling of the lube production plant”, (Chemical Engineering Communications, 192, 1067-1084, 2005).

II.30 Alexandridis, Α., H. Sarimveis, “A nonlinear adaptive MPC framework based on self-correcting RBF network models”, (AICHE Journal, 51(9), 2495-2506, 2005).

II.31 G. Melagraki, Afantitis Α., H. Sarimveis, O. Iglessi-Markopoulou, C. T. Supuran, “QSAR study on para – substituted aromatic sulfonamides as carbonic anhydrase II inhibitors using topological information indices”, (Bioorganic & Medicinal Chemistry, 14(4), 1108-1114, 2006).

II.32 Sarimveis, H., P. Doganis, A. Alexandridis, “A classification technique based on radial basis function neural networks”, (Advances in Engineering Software, 37(4), 218-221, 2006).

II.33 Doganis Ph., A. Alexandridis, P. Patrinos, H. Sarimveis, “Time series sales forecasting for short shelf-life food products based on artificial neural networks and evolutionary computing”, (Journal of Food Engineering, 75(2), 196-204, 2006).

II.34 G. Melagraki, Afantitis Α., K. Makridima, H. Sarimveis, O. Iglessi-Markopoulou “Prediction of toxicity using a novel RBF neural network training methodology”, (Journal of Molecular Modeling, 12(3), 297-305, 2006).

II.35 Aggelogiannaki E., H. Sarimveis, “Multiobjective constrained MPC with simultaneous closed loop identification”, (International Journal of Adaptive Control and Signal Processing, 20(4), 145-173, 2006).

II.36 A. Afantitis, Melagraki G., H. Sarimveis, P. A. Koutentis, J Markopoulos, O. Iglessi-Markopoulou, "Prediction of the Intrinsic Viscosity of Polymer – Solvent Combinations using a QSPR model",(Polymer, 47(9), 3240-3248, 2006).

II.37 Keramitsoglou I., H. Sarimveis, C. T. Kiranoudis, Ch. Kontoes, N. Sifakis, E. Fitoka, “The performance of pixel window algorithms in the classification of habitats using VHSR imagery”, (ISPRS Journal of Photogrammetry and Remote Sensing, 60(4), 225-238, 2006).

II.38 A. Afantitis, Melagraki G., H. Sarimveis, P. A. Koutentis, J Markopoulos, O. Iglessi-Markopoulou, "Investigation of Substituent Effect of 1-(3,3-Diphenylpropyl)-Piperidinyl Phenylacetamides Amides on CCR5 Binding Affinity using QSAR and Virtual Screening Techniques",(Journal of Computer-Aided Molecular Design, 20, 83-95, 2006).

II.39 G. Melagraki, Afantitis Α., H. Sarimveis, O. Iglessi-Markopoulou, A. Alexandridis “A novel RBF neural network training methodology to predict toxicity to Vibrio fischeri, (Molecular Diversity , 10(2), 213-221, 2006).

II.40 A. Afantitis, Melagraki G., H. Sarimveis, P. A. Koutentis, J Markopoulos, O. Iglessi-Markopoulou, " A Novel QSAR Model for Predicting Induction of Apoptosis by 4-Aryl-4H-chromenes",(Bioorganic and Medicinal Chemistry, 14, 6686-6694, 2006).

II.41 A. Afantitis, Melagraki G., H. Sarimveis, P. A. Koutentis, J Markopoulos, O. Iglessi-Markopoulou, “A Novel Simple QSAR Model for the Prediction of anti-HIV Activity Using Multiple Linear Regression Analysis”, (Molecular Diversity , 10, 405-414, 2006).

II.42 A. Afantitis, Melagraki G., H. Sarimveis, P. A. Koutentis, J Markopoulos, O. Iglessi-Markopoulou, "A Novel QSAR Model for Evaluating and Predicting the Inhibition Activity of Dipeptidyl Aspartyl Fluoromethylketones",(QSAR & Combinatorial Science, 10, 928-935, 2006).

II.43 Nikolakopoulos A., H. Sarimveis, “A Threshold Accepting Heuristic with intense Local Search for the Solution of Special Instances of the Traveling Salesman Problem”, (European Journal of Operations Research, 177(3), 1911-1929, 2007).

II.44 Melagraki G., A. Afantitis, H. Sarimveis, P. A. Koutentis, J Markopoulos, O. Iglessi-Markopoulou, " A novel QSPR model to predict θ(lower critical solution temperature) in polymer solutions using molecular descriptors", (Journal of Molecular Modeling, 13(1), 55-64, 2007).

II.45 Ph. Doganis, H. Sarimveis, “Optimal scheduling in a yogurt production line based on mixed integer linear programming”, (Journal of Food Engineering, 80, 445-453, 2007).

II.46 Melagraki G., A. Afantitis, H. Sarimveis, P. A. Koutentis, J Markopoulos, O. Iglessi-Markopoulou, "Optimization of Biaryl Piperidine and 4-Amino-2-biarylurea MCH1 Receptor Antagonists using QSAR Modeling, Classification Techniques and Virtual Screening", (Journal of Computer-Aided Molecular Design, 21(5), 251-267, 2007).

II.47 Aggelogiannaki E., H. Sarimveis, D. Koubogiannis, "Model Predictive Temperature Control in Long Ducts by means of a neural network approximation tool", (Applied Thermal Engineering, 27, 2363-2369, 2007).

II.48  E. Aggelogiannaki, H. Sarimveis,  “A simulated annealing algorithm for prioritized multiobjective optimization – Implementation in an adaptive model predictive control configuration”, (IEEE Transactions on Systems, Man, and Cybernetics--Part B, 37(4), 902-915 2007).

II.49 Melagraki G., A. Afantitis, H. Sarimveis, P. A. Koutentis, J Markopoulos, O. Iglessi-Markopoulou, " Identification of a series of novel derivatives as potent HCV inhibitors by a ligand – based virtual screening optimized procedure", (Bioorganic and Medicinal Chemistry, 15, 7237-7247, 2007).

II.50 Maglogiannis I., H. Sarimveis, C. T. Kiranoudis, H. A. Chatzioannou, N. Oikonomou, V. Aidinis, “Radial Basis Function neural networks classification for the recognition of idiopathic pulmonary fibrosis in microscopic images”, (IEEE Transactions on Information Technology in Biomedicine, 12(1), 42-54, 2008).

II.51 Doganis Ph., H. Sarimveis, “Optimal production scheduling for dairy industries”, (Annals of Operations Research, 159(1), 315-331, 2008).

II.52 Nikolakopoulos A, H. Sarimveis, “A Metaheuristic Approach for the Sequencing by Hybridization Problem with Positive and Negative Errors”, (Engineering Applications of Artificial Intelligence, 21(2), 247-258, 2008).

II.53  H. Sarimveis, P. Patrinos, C. D. Tarantilis, C. T. Kiranoudis, “Dynamic modeling and control of supply chain systems: A review”, (Computers and Operations Research, 35, 3530-3561, 2008).

II.54 Aggelogiannaki E., H. Sarimveis, " Nonlinear Model Predictive Control for Distributed Parameter Systems using Data Driven Artificial Neural Network Models",(Computers & Chemical Engineering, 32, 1233-1245, 2008).

II.55 P. L. Zervas, H. Sarimveis, J. A. Palyvos,  N. C. G. Markatos, “Prediction of Daily Total Solar Radiation on Horizontal Surfaces Based on Neural-Network Techniques”, (Renewable Energy, 33, 1796-1803, 2008).

II.56 A. Afantitis, Melagraki G., H. Sarimveis, P. A. Koutentis, J Markopoulos, O. Iglessi-Markopoulou, "Development and Evaluation of a QSPR Model for the Prediction of Diamagnetic Susceptibility”, (QSAR & Combinatorial Science, 27(4), 432-436, 2008).

II.57 P. L. Zervas, H. Sarimveis, J. A. Palyvos, N. C. G. Markatos, “Model-Based Optimal Control of a Hybrid Power Generation System consisting of Photovoltaic Arrays and Fuel Cells”,  (Journal of Power Sources, 181, 327-338, 2008).

II.58 E. Aggelogiannaki, Ph. Doganis, H. Sarimveis, " An Adaptive Model Predictive Control configuration for Production- Inventory Systems", (International Journal of Production Economics, 114, 165-178, 2008).

II.59 E. Aggelogiannaki, H. Sarimveis, " Design of a Novel Adaptive Inventory Control System Based on the On-Line Identification of Lead Time”, (International Journal of Production Economics, 114, 781-792, 2008).

II.60 P. L. Zervas, A. Tatsis, H. Sarimveis, N. C. G. Markatos, “Development of a novel computational tool for optimizing the operation of fuel cells systems: Application for Phosphoric Acid Fuel Cells”,  (Journal of Power Sources, 185(1), 345-355, 2008).

IΙ.61 Doganis Ph., E. Aggelogiannaki, H. Sarimveis, "A combined model predictive control and time series forecasting framework for production-inventory systems”, (International Journal of Production Research, 46(24), 6841-6853, 2008).

IΙ.62 A. Afantitis, Melagraki G., H. Sarimveis, O. Iglessi-Markopoulou, G. Kollias, "A novel QSAR model for predicting the inhibition of CXCR3 receptor by 4-N-aryl-[1,4] diazepane ureas”, (European Journal of Medicinal Chemistry, 44(2), 877-884, 2009).

II.63 E. Aggelogiannaki, H. Sarimveis, "Robust nonlinear H¥ control of hyperbolic distributed parameter systems”, (Control Engineering Practice, 17(6), 723-732, 2009).

II.64 J. Hasikos, H. Sarimveis, P. L. Zervas, N. C. G. Markatos, “Operational optimization and real-time control of fuel cell systems”,  (Journal of Power Sources, 193(1), 258-268, 2009).

IΙ.65 A. Afantitis, Melagraki G., H. Sarimveis, P. A. Koutentis,  G. Kollias, O. Iglessi-Markopoulou, "Predictive QSAR workflow for the in silico identification and screening of novel HDAC inhibitors" (Molecular Diversity, 13(3), 301-311, 2009).

IΙ.66 G.M. Stavrakakis, Zervas P. L., H. Sarimveis, N. C. Markatos " Development of a computational tool to quantify architectural-design effects on thermal comfort in naturally ventilated rural houses " (Building and Environment, 45(1), 65-80, 2010).

IΙ.67 E.D. Mehleri, Zervas P. L., H. Sarimveis, J.A. Palyvos, N. C. Markatos "A new neural network model for evaluating the performance of various hourly slope irradiation models: Implementation for the region of Athens" (Renewable Energy, 35(7), 1357-1362, 2010).

IΙ.68 G. Melagraki, Afantitis A., H. Sarimveis, P. A. Koutentis, O. Iglessi-Markopoulou, G. Kollias, " A combined LS-SVM & MLR QSAR workflow for predicting the inhibition of CXCR3 receptor by quinazolinone analogs " (Molecular Diversity, 14, 225-235, 2010).

IΙ.69 E.D. Mehleri, Zervas P. L., H. Sarimveis, J.A. Palyvos, N. C. Markatos "Determination of the optimal tilt angle and orientation for solar photovoltaic arrays" (Renewable Energy, 35, 2468-2475, 2010).

IΙ.70 P. Patrinos, H. Sarimveis, “A new algorithm for solving convex parametric quadratic programs based on graphical derivatives of solution mappings” (Automatica, 46(9), 1405-1418, 2010).

IΙ.71 Barry Hardy, Nicki Douglas, Christoph Helma, Micha Rautenberg, Nina Jeliazkova, Vedrin Jeliazkov, Ivelina Nikolova, Romualdo Benigni, Olga Tcheremenskaia, Stefan Kramer, Tobias Girschick, Fabian Buchwald, Joerg Wicker, Andreas Karwath, Martin Gutlein, Andreas Maunz, Haralambos Sarimveis, Georgia Melagraki, Antreas Afantitis, Pantelis Sopasakis, David Gallagher, Vladimir Poroikov, Dmitry Filimonov, Alexey Zakharov, Alexey Lagunin, Tatyana Gloriozova, Sergey Novikov, Natalia Skvortsova, Dmitry Druzhilovsky, Sunil Chawla, Indira Ghosh, Surajit Ray, Hitesh Patel and Sylvia Escher, “Collaborative development of predictive toxicology applications”, (Journal of Cheminformatics, 2:7, 2010).

IΙ.72 P. Patrinos, A. Alexandridis, K. Ninos, H. Sarimveis, “Variable selection in nonlinear modeling based on RBF networks and evolutionary computation” (International Journal of Neural Systems, 20(5), 365-379, 2010).

II.73 G. Melagraki, A. Afantitis, H. Sarimveis, O. Igglessi-Markopoulou, P. A. Koutentis and G. Kollias, “Exploration for Identifying Structure–Activity Relationship of MEK Inhibition and Oral Bioavailability for Isothiazole Derivatives”, (Chemical Biology and Drug Design, 76(5), 397-406, 2010).

IΙ.74 G.M. Stavrakakis, D.P. Karadimou, P.L. Zervas, H. Sarimveis, N.C. Markatos, “Selection of window sizes for optimizing occupational comfort and hygiene based on computational fluid dynamics and neural networks” (Building and Environment, 46(2), 298-314, 2011).

II.75 A. Afantitis,G. Melagraki,P. A. Koutentis,H. Sarimveis, G. Kollias, “Ligand - based virtual screening procedure for the prediction and the identification of novel <beta>-amyloid aggregation inhibitors using Kohonen Maps and Counterpropagation Artificial Neural Networks” (European Journal of Medicinal Chemistry, 46, 497-508, 2011).

II.76 A. Alexandridis, H. Sarimveis, K. Ninos, “A Radial Basis Function network training algorithm using a non-symmetric partition of the input space – Application to a Model Predictive Control configuration” (Advances in Engineering Software, 42(10), 830-837, 2011).

IΙ.77 P. Patrinos, H. Sarimveis, “Convex parametric piecewise quadratic optimization: Theory and algorithms” (Automatica, 47(8), 1770-1777, 2011).

IΙ.78 P. Patrinos, P. Sopasakis, H. Sarimveis, “A global piecewise smooth Newton method for fast large-scale model predictive control” (Automatica, 47(9), 2016-2022, 2011).

IΙ.79 G.M. Stavrakaksi, P.L. Zervas, H. Sarimveis, N.C. Markatos, “Optimization of window-openings desing for thermal comfort in naturally ventilated building” (Applied Mathematical Modelling, 36(1), 193-211, 2012).

II.80 E. D. Mehleri, H. Sarimveis, N. C. Markatos,  L. G. Papageorgiou, “A mathematical programming approach for optimal design of distributed energy systems at the neighbourhood level”, (Energy, 44(1), 96-104, 2012).

II.81 P. Sopasakis, H. Sarimveis, “"An Integer Programming Approach for Optimal Drug Dose Computation" (Computer Methods and Programs in Biomedicine, 108, 1022-1035, 2012).

II.82 E. D. Mehleri, H. Sarimveis, N. C. Markatos,  L. G. Papageorgiou, “Optimal design and operation of distributed energy systems: Application to Greek residential sector”, (Renewable Energy, 51, 331-342, 2013).

II.83 A. Alexandridis, E. Chondrodima, H. Sarimveis “Radial Basis Function network training using a non-symmetric partition of the input space and Particle Swarm Optimization”, (IEEE Transactions on Neural Networks and Learning Systems, 24(2), 219-230, 2013).

II.84 A. Alexandridis, M. Stogiannos, A. Kyriou, H. Sarimveis, “An offset-free neural controller based on a non-extrapolating scheme for approximating the inverse process dynamics”, Journal of Process Control”, (Journal of Process Control, 23, 968-979, 2013).

IΙ.85 P. Sopasakis, P. Patrinos, H. Sarimveis, “MPC for sampled-data linear systems: Guaranteeing constraint satisfaction in continuous-time” (IEEE Transactions on Automatic Control, accepted for publication).

IΙ.86 Ph. Doganis, H. Sarimveis, “Optimization of power production through coordinated use of hydroelectric and conventional power units” (Applied Mathematical Modelling, Volume 38, Issues 7–8, 2051–2062, 2014).

IΙ.87 P. Patrinos, P. Sopasakis, H. Sarimveis, A. Bemporad, “Stochastic model predictive control for constrained discrete-time Markovian switching systems” (Automatica, 50, 2504-2514, 2014).

IΙ.88 P. Sopasakis, P. Patrinos, H. Sarimveis, “Robust Model Predictive Control for Optimal Continuous Drug Administration” (Computer Methods and Programs in Biomedicine, 116(3), 193-204, 2014).

IΙ.89 P. Sopasakis, P. Patrinos, H. Sarimveis, A. Bemporad, “Model Predictive Control for Linear Impulsive Systems” (IEEE Transactions on Automatic Control, 60(8), 2277-2282, 2015).

ΙΙ.90 N. Jeliazkova, C. Chomenidis, P. Doganis, B. Fadeel, R. Grafström, B. Hardy, J. Hastings, M. Hegi, V. Jeliazkov, N. Kochev, P. Kohonen, C. R. Munteanu, H. Sarimveis, B. Smeets, P. Sopasakis, G. Tsiliki, D. Vorgrimmler, E. Willighagen, “The eNanoMapper database for nanomaterial safety information”, (Beilstein Journal of Nanotechnology 1609-1634, 2005)

II.91 G. Tsiliki, C. R. Munteanu, J. A Seoane, C. Fernandez-Lozano, H. Sarimveis,  E. L. Willighagen, “RRegrs: An R package for Computer-aided Model Selection with Multiple Regression Models”, (Journal of Cheminformatics, 7:46, 2015

 

III. Conference Proceedings Publications

 III.1 Nikolaou, M., and H. Sarimveis, “Process modeling with recurrent neural networks”, ANNIE, St. Louis, MO, 1991.

III.2 Sarimveis, H., H. Genceli and M. Nikolaou, “Rigorous design of robust model predictive controllers for processes with more inputs than outputs”, Escape- 6, Rhodes, Greece, 1996.

III.3 Sarimveis, H. and Th. Retsina, “Inferential sensors for on-Line monitoring of quality parameters in the pulp and paper industry”, AspenWorld 2000 Conference, 2000.

III.4 Alexandridis, A., Κ. Siettos, H. Sarimveis, A. Boudouvis and G. Bafas, “Modeling of nonlinear process dynamics using Kohonen’s neural Networks, fuzzy systems and Chebyshev series”, Escape- 11, Kolding, Denmark, 2001.

III.5 Sarimveis H. , A. Alexandridis, A.Angelou, and Th. Retsina “Artificial intelligence tools for the on-line prediction of quality properties in pulp and paper processes”, Paper Summit, Atlanta, GA, 2002.

III.6 Sarimveis H., A.Angelou, and Th. Retsina “Mill wide optimization based on mathematical   programming techniques”, Paper Summit, Atlanta, GA, 2002.

III.7 Alexandridis A., H. Sarimveis, A.Angelou Th. Retsina and G. Bafas “A Model Predictive Control    scheme for continuous pulp digesters based on the Partial Least Square (PLS) modeling algorithm ”,  Control Systems 2002, Stockholm, Sweden, 2002.

III.8 Sarimveis H., A.Angelou Th. Retsina, A. Alexandridis and G. Bafas, “A mathematical programming approach for the optimum production planning in pulp and paper mill”, Control Systems 2002, Stockholm, Sweden, 2002.

III.9 Sarimveis,H., A. Alexandridis, S.Mazarakis and G. Bafas, “A new algorithm for developing dynamic radial basis function neural network models based on genetic algorithms”, ESCAPE-12, The Hague, Netherlands, 2002.

III.10 Sarimveis H., A. Alexandridis and G. Bafas, “Neural network model identification based on the subtractive clustering method”, IFAC World Congress, Barcelona, Spain, 2002.

III.11 Alexandridis A., H. Sarimveis, G. Bafas and Th. Retsina “A neural network approach for modeling and control of continuous digesters” TAPPI Fall Conference, San Diego, CA, 2002.

III.12 Alexandridis A., H. Sarimveis, G. Bafas, “Adaptive control of continuous pulp digesters based on radial basis function neural network models” ESCAPE 13, Lappeenranta, Finland, 2003.

III.13 Alexandridis A., H. Sarimveis, G. Bafas, “A new nonlinear adaptive model predictive control scheme based on RBF neural network models”, 3rd Chemical Engineering Conference for Collabororative Research in Eastern Mediterranean, Thessaloniki, Greece, 2003.

III.14 Alexandridis A., H. Sarimveis, G. Bafas, “Modeling of continuous digesters using adaptive RBF neural network models”, 11th Mediterranean Conference on Control and Automation MED'03, Rhodes, Greece, 2003.

III.15 Keramitsoglou I., H. Sarimveis, C. T. Kiranoudis, N. Sifakis, “Ecosystem classification using artificial intelligence neural networks and very high spatial resolution satellite imagery”, Remote Sensing 2003, Barcelona, Spain, 2003.

III.16 Patrinos P, A. Alexandridis, A. Afantitis, H. Sarimveis and O. Igglesi-Markopoulou, “Development of nonlinear Quantitative Structure-Activity Relationships using RBF networks and evolutionary computing”, ESCAPE 14, Lisbon, Portugal, 2004.

III.17 Aggelogiannaki E., H. Sarimveis and G. Bafas, “Multiobjective constrained MPC with simultaneous closed loop identification for MIMO processes”, ESCAPE 14, Lisbon, Portugal, 2004.

III. 18 Patrinos P, H. Sarimveis, “An RBF based neuro-dynamic approach for the control of stochastic dynamic systems”, IFAC World Congress 2005, Prague, Czech Republic, 2005.

III. 19 Aggelogiannaki E., H. Sarimveis, A. Alexandridis, “A prioritized Multiobjective MPC configuration using adaptive RBF networks and evolutionary computation, IFAC World Congress 2005, Prague, Czech Republic, 2005.

III. 20  Doganis, Ph., H. Sarimveis, G. Bafas, “Optimal production scheduling for dairy industries based on a neural network sales forecasting model”, IMACS 2005, Paris, France, 2005

III. 21  P. Patrinos, H. Sarimveis, Th. Retsina, S. Rutherford, A. Alexandridis, “Neural network model-based paper machine marginal cost curves” Engineering, Pulping, Environmental TAPPI 2005 Conference, Philadelphia, PA, USA, 2005.

III. 22 Aggelogiannaki, E. H. Sarimveis “Model Predictive Control for Distributed Parameter Systems using RBF neural networks”, ICINCO 2005, Barcelona, Spain, 2005.

III. 23  Aggelogiannaki E., H. Sarimveis “Prioritized adaptive Model Predictive Control using evolutionary algorithms”,   5th International Conference on Technology and Automation    ICTA'05, Thessaloniki, Greece, 2005. 

III. 24 Aggelogiannaki E., H. Sarimveis, “Affine Radial Basis Function Neural Networks for the Robust Control of Hyperbolic Distributed Parameter Systems”, ICRA 2006 : "International Conference on Intelligent Control, Robotics and Automation”, Barcelona, Spain, 2006.

III. 25 Doganis Ph., Aggelogiannaki E., H. Sarimveis, “A model predictive control and time series forecasting framework for supply chain management”, ICRA 2006 : "International Conference on Intelligent Control, Robotics and Automation”, Barcelona, Spain, 2006.

III. 26 Patrinos P, H. Sarimveis, “An explicit optimal control approach for mean-risk dynamic portfolio allocation”, European Control Conference (ECC 2007), Kos, 2007.

III. 27  P.L Zervas, H. Sarimveis, J.Α. Palyvos, N.C. Markatos, “Development of an Efficient Real-Time Optimization Strategy for a Hybrid Power Generation System consisting of Photovoltaic Arrays and Fuel Cells (PV-FC)”,  ENERTECH 2007, Athens, 2007.

III.28 E.D. Mehleri, P.L. Zervas, H. Sarimveis, J.A. Palyvos, N.C. Markatos, “Classification of Global Solar Irradiance Decomposition Models and Development of a New Empirical Model: Implementation for the region of Athens, Greece”, World Renewable Energy Congress, Glasgow, Scotland, 2008

III.29 H. Sarimveis, P. Sopasakis, A. Afantitis, G.Melagraki, “A Model Predictive Control Approach for Optimal Drug Administration”, The ninth International Conference on
Chemical & Process Engineering, Rome, Italy, 2009.

III.30 E. Aggelogiannaki, H. Sarimveis, “Nonlinear robust control of parabolic distributed parameter systems by means of radial basis function neural networks and singular value decomposition”, European Control Conference (ECC2009), 2009.

III.31 P. Sopasakis, P. Patrinos, S. Giannikou, H. Sarimveis, “Physiologically Based Pharmacokinetic Modeling and Predictive Control: An Integrated Approach,” ESCAPE 21, Chalkidiki, Greece, 2011.

III.32 E. D. Mehleri, H. Sarimveis, N. C. Markatos,  L. G. Papageorgiou, “Optimal Design and Operation of Distributed Energy Systems”, ESCAPE-21 Conference, Chalkidiki, Greece, 2011.

III.33 A. Alexandridis, H. Sarimveis, “Control of Multiple Steady State Processes using MPC and RBF Neural Networks,” ESCAPE 21, Chalkidiki, Greece, 2011.

III.34 P. Patrinos, P. Sopasakis, H. Sarimveis, “Stochastic Model Predictive Control for Constrained Networked Control Systems with Random Time Delay”, 18th IFAC World Congress, Milan, 2011.

III.35 E. D. Mehleri, L. G. Papageorgiou,  N. C. Markatos. H. Sarimveis, “A Model Predictive Control Framework for Residential Microgrids”, ESCAPE-22 Conference, London, UK, 2012.

III.36 E. D. Mehleri, H. Sarimveis, L. G. Papageorgiou,  N. C. Markatos., “Model predictive control of distributed energy resources”, 20th Mediterranean Conference on Control and Automation, Barcelona, Spain, 2012.

III.37 P. Sopasakis, P. Patrinos, H. Sarimveis, A. Bemporad, “Model Predictive Control for Linear Impulsive Systems”, 51st IEEE Conference on Decision and Control, Maui, Hawaii, USA, 2012.

III.38 P. Sopasakis, H. Sarimveis, “ToxOtis: A Java Interface to the OpenTox Predictive Toxicology Network”, CEMEPE/SECOTOX 2013 Conference, Mykonos, Greece, 2013.

III.39 I. Bonis, H. Sarimveis, D.G. Koubogiannis, “Proper Orthogonal Decomposition-based reduced order modelling of vortex shedding”, 5th International Conference on Experiments/Process/Systems Modelling/Simulation/Optimization (IC-EpsMsO), Athens, Greece, 2013.

III.40 P. Sopasakis, H. Sarimveis, “Controlled drug administration by a fractional PID”, 19th IFAC World Congress, Cape Town, South Africa, 2014.
III. 41 A. Alexandridis, M. Stogiannos, A. Loukidis, K. Ninos, E. Zervas, H. Sarimveis, “Direct versus Indirect Neural Control based on Radial Basis Function Networks”,  CEEC 2014 : 6th Computer Science and Electronic Engineering Conference, Colchester, UK, 2014.

III. 42 A. Alexandridis, E. Chondrodima, G. Paivana, M. Stogiannos, E. Zois, H. Sarimveis, “Music Genre Classification Using Radial Basis Function Networks and Particle Swarm Optimization”, CEEC 2014 : 6th Computer Science and Electronic Engineering Conference, Colchester, UK, 2014.

III. 43 N Jeliazkova, V. Jeliazkov, E. Willighagen, B. Smeets, C. Munteanu, B. Fadeel, R. Grafström, P. Kohonen, H. Sarimveis, G. Tsiliki, Ph. Doganis, D. Vorgrimmler, J. Hastings, “The first eNanoMapper prototype: a substance database to support safe-by-design”, Nanoinformatics for Environmental Health and Biomedicine (NanoInfo2014), Belfast, UK, 2014.

III. 44 N. Vlachou, A. Trompeta, H. Sarimveis, C.A. Charitidis, “Life Cycle Assessment as a Prerequisite Tool in Maritime Industry”, 2015 International Conference on Energy and Environment in Ships, Athens, Greece, 2015.

III. 45  E. Anagnostopoulou, S. Ntouskas, P. Sopasakis, H. Sarimveis, “A web application for determination of optimal drug dosing without violating toxicity constraints”, 5th International Conference on Environmental Management, Engineering, Planning and Economics (CEMEPE 2015) & SECOTOX Conference, Mykonos Island, Greece, 2015.

III.46 P. Sopasakis, S. Ntouskas, H. Sarimveis, “Robust Model Predictive Control for Discrete-time Fractional-order Systems”, MED2015-23rd Mediterranean Conference on Control and Automation, Torremolinos, Spain, 2015.

III.47 I. Bonis, H. Sarimveis, D.G. Koubogiannis, “Optimal control of vortex shedding using detailed models”, 8th GRACM International Congress on Computational Mechanics, Volos, 2015.

 

IV. Conference Presentations

IV.1 Nikolaou, M., and H. Sarimveis,. “Input-output exact linearization of nonlinear dynamical systems modeled by Recurrent Neural Networks”, AIChE Annual Meeting, Los Angeles, CA, 1992.

IV.2 Sarimveis, H., H. Genceli and M. Nikolaou,. “Design of robust non-square constrained model predictive control”, AIChE Annual Meeting, Miami, FL, 1995.

IV.3 Sarimveis, H., “Inferential neural network sensors for on-line prediction of tissue paper quality parameters”, AIChE Annual Meeting, Dallas, TX, 1999.

IV.4 Sarimveis,H., A. Angelou, J. Thanassekos and Th. Retsina, “Mill wide optimization using mixed integer and linear programming techniques”, PAPTAC MIDWEST BRANCH, 54th Annual Meeting, Quebec, Canada, 2000.

IV.5 Sarimveis, H. and Th. Retsina, “Tissue softness prediction using neural network methodologies”, 86th Annual Meeting of the Pulp and Paper Technical Association of Canada, Montral, Canada, 2000.

IV.6 Sarimveis, H., A. Angelou, Th. Retsina “Optimization of the powerhouse operation in pulp and paper mills using mixed integer and linear programming techniques”, 51st Canadian Chemical Engineering  Conference, Halifax, Canada, 2001.

IV.7 Sarimveis,H., A. Alexandridis A., G. Bafas, J. Thanassekos and Th. Retsina,  “Multi-period optimization methodology for planning and scheduling of pulp and paper mills”, AIChE Annual Meeting, Reno, NV, 2001.

IV.8 Melagraki, G., K. Makridima, A. Afantitis, H. Sarimveis and O. Igglesi-Markopoulou, “A novel QSTR model to predict toxicity of aromatic compounds based on the RBF neural network architecture”, The 11th International Workshop on Quantitative Structure-Activity Relationships in Environmental Sciences (QSAR 2004), Liverpool, England, 2004.

IV.9 Makridima K., A. Afantitis, G. Melagraki, P. Patrinos, H. Sarimveis and O. Igglesi-Markopoulou, “Using the Radial Basis Function (RBF) neural network architecture to develop QSARs for the prediction of the toxicity of phenols in Tetrahymena pyriformis”, The 11th International Workshop on Quantitative Structure-Activity Relationships in Environmental Sciences (QSAR 2004), Liverpool, England, 2004.

IV.10 Afantitis, A., G. Melagraki, K. Makridima, H. Sarimveis and O. Igglesi-Markopoulou, “A QSTR model for the prediction of paraffins and cycloalkanes boiling points using RBF neural networks and topological indices”, The 11th International Workshop on Quantitative Structure-Activity Relationships in Environmental Sciences (QSAR 2004), Liverpool, England, 2004.

IV.11 Afantitis, A., G. Melagraki, K. Makridima, H. Sarimveis and O. Igglesi-Markopoulou, “A QSPR model for the prediction of polyacenes properties using  RBF neural networks and topological indices”, The 11th International Workshop on Quantitative Structure-Activity Relationships in Environmental Sciences (QSAR 2004), Liverpool, England, 2004.

IV.12 Vakalis, D., H. Sarimveis, C.T. Kiranoudis, A. Alexandridis, G. Bafas, “Modeling and Simulation of Wildfires based on Artificial Intelligence Techniques”,  ICCMSE, Athens, Greece, 2004.

IV.13 G. Melagraki, A. Afantitis, H. Sarimveis, O. Igglesi-Markopoulou, J. Markopoulos. Carbonic Anhydrase II Inhibitors: QSAR study using topological indices for a large set of sulfonamides.  6th Medicinal Chemistry Conference: Medicinal Chemistry Drug Discovery and Design, 2005.

IV.14 A. Afantitis, G. Melagraki, H. Sarimveis, O. Igglesi-Markopoulou, J. Markopoulos. A novel approach to build QSAR models for a large group of HEPT derivatives. 6th Medicinal Chemistry Conference : Medicinal Chemistry Drug Discovery and Design, 2005. 

IV.15 K,Makridima, A. Afantitis, G. Melagraki, H. Sarimveis, O. Igglesi-Markopoulou, A QSAR study on the inhibitory activity of set of compounds (1-phenylbenzimidazoles) against the platelet – derived growth factor receptor (PDGFR). 6th Medicinal Chemistry Conference: Medicinal Chemistry Drug Discovery and Design, 2005.

IV.16 I. Maglogiannis, C. Kiranoudis, H. Sarimveis, “Classification of microscopic images using radial basis function neural networks”, 2nd IEEE International Conference on Computational Intelligence in Medicine and Healthcare, Lisbon, Portugal, 2005.

IV.17 G. Melagraki, A. Afantitis, H. Sarimveis, P.A Koutentis, O. Igglesi-Markopoulou and J. Markopoulos.” Density Functional Theory study of 3-acyl tetramic acids complexes with metal ions” 8th FIGIPAS Meeting in Inorganic Chemistry, Athens, Greece, 2005.

IV.18 Ph. Doganis, H. Sarimveis, G. Bafas, “Optimal production scheduling for dairy industries based on a neural networks sales forecasting model”, MISTA 2005 The 2nd Multidisciplinary International Conference on Scheduling: Theory and Applications, NY, NY, USA,  2005.

IV.19 A. Nikolakopoulos, H. Sarimveis, “On the Formulation of the DNA Sequencing by Hybridization problem as an Asymmetric Traveling Salesman problem”, MISTA 2005 The 2nd Multidisciplinary International Conference on Scheduling: Theory and Applications, NY, NY, USA,  2005.

IV. 20 A. Afantitis, G. Melagraki, H. Sarimveis, P.A Koutentis,  J. Markopoulos, O. Igglessi-Markopoulou “Investigation of Substituent Effect of Thiazole and Oxodiazole Butanoic Acids as Potent ανβ3 receptor antagonists using QSAR and Virtual Screening Techqiques” International Symposium on Chemistry, Biology & Chemistry, Paphos, Cyprus, 2006. 

IV. 21 G. Melagraki, A. Afantitis, H. Sarimveis, P.A Koutentis,  J. Markopoulos, O. Igglessi-Markopoulou “Virtual Screening of Biaryl Piperidine and 4-Amino-2-Biarylbutylureas as MCH1 Receptor Antagonists Using a Validated QSAR Model and Pharmacophore” International Symposium on Chemistry, Biology & Chemistry, Paphos, Cyprus, 2006.

IV. 22 Nikolakopoulos A, H. Sarimveis, “A Heuristic approach to the Vehicle Routing Problem with Time Windows and Simultaneous Pick-up and Delivery”, Third international workshop on freight transportation and logistics- ODYSSEUS 2006, Altea, Spain, 2006.

IV. 23 P.L Zervas, H. Sarimveis, J.Α. Palyvos, N.C. Markatos, “Model-based Optimal Control of a Hybrid Power Generation System consisting of Photovoltaic Arrays and Fuel Cells (PV-FC)”, 10th Grove Fuel Cell Symposium, London, 2007.

IV. 24 P.L Zervas, H. Sarimveis, J.Α. Palyvos, N.C. Markatos, “Optimal decision strategy for a renewable energy system consisting of wind generators and fuel cell stacks”, Fuel Cells Science & Technology 2008 - Scientific Advances in Fuel Cell Systems, Copenhagen, 2008.

IV. 25 P.L Zervas, H. Sarimveis, J.Α. Palyvos, N.C. Markatos, “Operational optimization and real-time control of fuel cell systems: Application for phosphoric acid fuel cells”, Fuel Cells Science & Technology 2008 - Scientific Advances in Fuel Cell Systems, Copenhagen, 2008.

IV. 26 P.L Zervas, H. Sarimveis, J.Α. Palyvos, N.C. Markatos, “Model-based optimal control of hybrid renewable energy systems”, Second International Conference on Environmental Management, Engineering, Planning and Economics (CEMEPE 09) & SECOTOX Conference, Mykonos, 2009.

IV. 27 E.D. Mehleri, P.L Zervas, H. Sarimveis, J.Α. Palyvos, N.C. Markatos, “Unit Sizing and Cost Analysis of a stand-alone PV/Fuel Cell Power Generation System”, 11th Grove Fuel Cell Symposium, London, 2009.

IV. 28  G. Melagraki, P. Sopasakis, A. Afantitis, H. Sarimveis “Consensus QSAR Modeling and domain of applicability: An integrated approach”, 18th European Symposium on Quantitative Structure-Activity Relationships, Rhodes , Greece, 2010.

IV.29 A. Afantitis, G. Melagraki, H. Sarimveis,  Zhang Liying, Zhu Hao, A. Tropsha,“Combinatorial QSAR Modeling of toxicity data using 2D & 3D chemical descriptors”, 18th European Symposium on Quantitative Structure-Activity Relationships, Rhodes , Greece, 2010.

IV.30  E. D. Mehleri, H. Sarimveis, N. C. Markatos,  L. G. Papageorgiou, “Design and operational optimization of a heating pipeline network within a microgrid”, SET2011, 10th International Conference on Sustainable Energy Technologies, Turkey, 4-7 Sep. 2011.

IV.31 P. Sopasakis, H. Sarimveis, “JAQPOT RESTful Web Services: An Implementation of the OpenTox Application Programming Interface for On-line Prediction of Toxicological Properties”, CEMEPE/SECOTOX 2013 Conference, Mykonos, Greece, 2013.

IV.32 P. Sopasakis, H. Sarimveis, “Fractional-Order pharmacokinetics and control”, OpenTox Euro2013,Mainz, Germany, 2013.

IV.33 C. R. Munteanu, H. Sarimveis, “Prediction of EC50 values for fullerenes using Markov Mean Properties and assay conditions”, NanoTox 2014, Antalya, Turkey, 2014.

IV.34. S. Ntouskas, P. Sopasakis, H. Sarimveis, “A web-based software tool for individualized drug dosing using PBPK models and control theory”, OpenTox 2014, Athens, Greece, 2014.

IV.35. G. Tsiliki, H. Sarimveis, “ManoQSAR modelling using protein corona fingerprints”, OpenTox 2014, Athens, Greece, 2014.

IV.36. S. Ntouskas, H. Sarimveis, “Model Predictive Control for Intravenous Bolus Administration of Medicines”, From Drug Dicovery to Delivery, Athens, Greece, 2014.

IV.37. M. Kotsiandris, P. Doganis, H. Chomenidis, G. Drakakis, P. Sopasakis, H. Sarimveis, “A web application for deriving descriptors of nanomaterials from the analysis of TEM images”, 12th International Conference on Nanosciences & Nanotechnologies (NN15), Thessaloniki, Greece, 2015.

IV. 38. H. Sarimveis,  P. Sopasakis, S. Ntouskas,  E. Anagnostopoulou,  Ch. Chomenidis,  “Drug dosing optimization strategies based on the model predictive control framework”, International Conference on Chemical and Biochemical Engineering, Paris, France, 2015.

IV. 39 B. Hardy, E.L. Willighagen, J. Hastings, M. Hegi, N. Jeliazkova, H. Sarimveis. “eNanoMapper: A database and ontology framework for nanomaterials design and safety assessment”, American Chemical Society National Meeting & Exposition, Boston, 2015.

V. Conference Presentations in Greece

V.1 Αλεξανδρίδης, Α., Χ. Σαρίμβεης και Γ. Μπάφας. «Εφαρμογή υβριδικής μεθόδου νευρωνικών δικτύων και μερικών ελαχίστων τετραγώνων στη δυναμική προσομοίωση χημικών διεργασιών», 3ο Πανελλήνιο συνέδριο Χημικής Μηχανικής, Αθήνα, 2001.

V.2 Χ. Σαρίμβεης, Α. Αλεξανδρίδης, και Γ. Μπάφας, «Ελαχιστοποίηση του κόστους παραγωγής σε βιομηχανικές μονάδες με εφαρμογή μεθοδολογίας μεικτού γραμμικού και ακέραιου προγραμματισμού», 3ο Πανελλήνιο συνέδριο Χημικής Μηχανικής, Αθήνα, 2001.

V.3 Χ. Σαρίμβεης και Μ. Νικολάου, «Εφαρμογές σύγχρονων υπολογιστικών συστημάτων στην αριστοποίηση και την αυτόματη ρύθμιση διεργασιών παραγωγής σνακ», 3ο Πανελλήνιο συνέδριο Χημικής Μηχανικής, Αθήνα, 2001.

V.4 Νικολακόπουλος Α, Χ. Σαρίμβεης και Γ. Μπάφας, «Ανάπτυξη ευρεστικού αλγόριθμου επίλυσης προβλημάτων μικτού ακέραιου και μη γραμμικού προγραμματισμού με εφαρμογή στην αριστοποίηση συστημάτων χημικής μηχανικής», 4ο Πανελλήνιο συνέδριο Χημικής Μηχανικής, Πάτρα, 2003.

V.5 Αλεξανδρίδης Α, Χ. Σαρίμβεης και Γ. Μπάφας, «Εκπαίδευση νευρωνικών δικτύων ακτινικής συνάρτησης βάσης με αλγόριθμο αφαιρετικής ομαδοποίησης», 4ο Πανελλήνιο συνέδριο Χημικής Μηχανικής, Πάτρα, 2003.

V.6 Δογάνης Φ, Χ. Σαρίμβεης, Γ. Μπάφας και Δ. Κουφός, «Βελτιστοποίηση της παραγωγικής διαδικασίας σε μονάδα παραγωγής λιπαντικών με χρήση μαθηματικού προγραμματισμού», 4ο Πανελλήνιο συνέδριο Χημικής Μηχανικής, Πάτρα, 2003.

V.7 Γ. Μελαγράκη, Κ. Μακρυδήμα, Α. Αφαντίτης, Χ. Σαρίμβεης, Ό. Ιγγλέση Μαρκοπούλου. Ανάπτυξη Μοντέλων QSTR για την Πρόβλεψη Τοξικότητας Ετερογενών Οργανικών Ενώσεων. 8ο Συνέδριο Χημείας Ελλάδος – Κύπρου με θέμα “Χημεία, Ποιότητα Ζωής και Εκπαίδευση”, Θεσσαλονίκη, 2004.

V.8 Α. Αφαντίτης, Γ. Μελαγράκη, Κ. Μακρυδήμα, Χ. Σαρίμβεης, Ό. Ιγγλέση Μαρκοπούλου. Ανάπτυξη Μοντέλου QSPR για την Πρόβλεψη της Θερμοκρασίας Υαλώδους Μετάπτωσης σε Πολυμερή με Μεγάλα Μοριακά Βάρη. “Χημεία, Ποιότητα Ζωής και Εκπαίδευση”, Θεσσαλονίκη, 2004. 

V.9 Κ. Μακρυδήμα, Α. Αφαντίτης, Γ. Μελαγράκη, Χ. Σαρίμβεης, Ό. Ιγγλέση Μαρκοπούλου. Ανάπτυξη Ποσοτικών Σχέσεων Δομής – Δραστικότητας για την Πρόβλεψη της Τοξικότητας Χλωριωμένων Ενώσεων με Χρήση Νευρωνικού Δικτύου RBF. 8ο Συνέδριο Χημείας Ελλάδος – Κύπρου με θέμα “Χημεία, Ποιότητα Ζωής και Εκπαίδευση”, Θεσσαλονίκη, 2004.

V.10 Γ. Μελαγράκη, Α. Αφαντίτης, Φ. Δογάνης, Χ. Σαρίμβεης, Ό. Ιγγλέση Μαρκοπούλου. Σχεδιασμός Μορίων Με επιθυμητή Δράση : Εφαρμογή στην Αριστοποίηση των Σουλφοναμιδίων ως Αναστολέων της Καρβονικής Ανυδράσης. 5ο Πανελλήνιο Επιστημονικό Συνέδριο Χημικής Μηχανικής, Θεσσαλονίκη, 2005.

V.11 Α. Αφαντίτης, Γ. Μελαγράκη, Α. Τσουμάνης Χ. Σαρίμβεης, Ό. Ιγγλέση Μαρκοπούλου. Ανάπτυξη Μοντέλου QSAR με χρήση Τοπολογικών Δεικτών για τη Πρόβλεψη της Ικανότητας Αναστολής του Ενζύμου Κασπάση. 5ο Πανελλήνιο Επιστημονικό Συνέδριο Χημικής Μηχανικής, Θεσσαλονίκη, 2005.

V.12 Φ. Δογάνης, Χ. Σαρίμβεης. Ανάπτυξη μοντέλου μεικτού ακέραιου και γραμμικού προγραμμτισμού για τη βελτιστοποίηση της παραγωγής σε βιομηχανία γαλακτοκομικών προιόντων. 5ο Πανελλήνιο Επιστημονικό Συνέδριο Χημικής Μηχανικής, Θεσσαλονίκη, 2005.

V.13 Ε. Αγγελογιαννάκη, Χ. Σαρίμβεης, «Aνάπτυξη ρυθμιστή προβλεπτικού μοντέλου για συστήματα κατανεμημένων παραμέτρων», 6ο Πανελλήνιο Επιστημονικό Συνέδριο Χημικής Μηχανικής, Αθήνα, 2007.

V.14 Α. Αλεξανδρίδης, Χ. Σαρίμβεης, Γ. Μπάφας, «Ανάπτυξη αλγορίθμου εκπαίδευσης νευρωνικών δικτύων ακτινικής συνάρτησης βάσης με μη συμμετρική διαμέριση του χώρου των μεταβλητών εισόδου», 6ο Πανελλήνιο Επιστημονικό Συνέδριο Χημικής Μηχανικής, Αθήνα, 2007.

V.15 Π. Πατρινός, Χ. Σαρίμβεης, «Εύρωστος βέλτιστος έλεγχος: υπολογισμός της ρητής έκφρασης του νόμου ανάδρασης συνδυάζοντας τον δυναμικό προγραμματισμό με την πολυπαραμετρικη βελτιστοποίηση», 6ο Πανελλήνιο Επιστημονικό Συνέδριο Χημικής Μηχανικής, Αθήνα, 2007.

V.16 Α. Γ. Τάτσης, Π. Λ. Ζέρβας, Χ. Σαρίμβεης, Μ. Κ. Κούκου, Ν. Χ. Μαρκάτος, «Ανάπτυξη ενός ολοκληρωμένου υπολογιστικού εργαλείου για την αριστοποίηση της λειτουργίας κελιών καυσίμου τύπου pafc», 6ο Πανελλήνιο Επιστημονικό Συνέδριο Χημικής Μηχανικής, Αθήνα, 2007.

V.17 Π. Λ. Ζέρβας, Χ. Σαρίμβεης, Ι. Α. Παλυβός, Ν. Χ. Μαρκάτος, «Μελέτη βελτιστοποίησης υβριδικής μονάδας ισχύος αποτελούμενης από φωτοβολταϊκη συστοιχία – κελιά καύσιμου (pv-fc), 6ο Πανελλήνιο Επιστημονικό Συνέδριο Χημικής Μηχανικής, Αθήνα, 2007.

V.18 Π. Σωπασάκης, Π. Πατρινός, Χ. Σαρίμβεης, «Εξαγωγή Ρητής Έκφρασης του Νόμου Ελέγχου Μη Γραμμικών Συστημάτων που υπόκεινται σε περιορισμούς συνδυάζοντας τον Ασαφή Προβλεπτικό Έλεγχο με τον Πολυπαραμετρικό Προγραμματισμό, 7ο Πανελλήνιο Επιστημονικό Συνέδριο Χημικής Μηχανικής, Πάτρα, 2009.

V.19 Π. Σωπασάκης, Χ. Σαρίμβεης, «Διαμόρφωση και επίλυση προβλήματος προβλεπτικού ελέγχου όπου οι μεταβλητές εκ χειρισμού λαμβάνουν τιμές από πεπερασμένα σύνολα», 7ο Πανελλήνιο Επιστημονικό Συνέδριο Χημικής Μηχανικής, Πάτρα, 2009.

V.20 Γ. Μ. Σταυρακάκης, Π. Λ. Ζέρβας, Χ. Σαρίμβεης, Ν. Χ. Μαρκάτος, «Ανάπτυξη υπολογιστικού μοντέλου για την ποσοτικοποίηση της επίδρασης του αρχιτεκτονικού σχεδιασμού στην θερμική άνεση φυσικά αεριζόμενου κτιρίου», 7ο Πανελλήνιο Επιστημονικό Συνέδριο Χημικής Μηχανικής, Πάτρα, 2009.

V.21 Ι. Σ. Βατόπουλος, Π. Λ. Ζέρβας, Χ. Σαρίμβεης, Ν. Χ. Μαρκάτος, «Διερεύνηση και Βελτιστοποίηση Λειτουργίας Κελιών Καυσίμου Φωσφωρικού Οξέος (PAFC) σε Πρότυπη Εγκατάσταση με χρήση Υπολογιστικού Ρευστοδυναμικού Μοντέλου και Αλγεβρικών συσχετίσεων», 7ο Πανελλήνιο Επιστημονικό Συνέδριο Χημικής Μηχανικής, Πάτρα, 2009.

V.22 Ε. Δ. Μέχλερη, Π. Λ. Ζέρβας, Χ. Σαρίμβεης, Ι. Α. Παλυβός, Ν. Χ. Μαρκάτος, «Μελέτη διαστατοποίησης ενός αυτόνομου φωτοβολταϊκού συστήματος στην περιοχή της Αθήνας», 7ο Πανελλήνιο Επιστημονικό Συνέδριο Χημικής Μηχανικής, Πάτρα, 2009.

V.23 Φ. Δογάνης, I. Bafumba, Χ. Σαρίμβεης, «Αριστοποίηση παραγωγής ηλεκτρικής ενέργειας από συντονισμένη αξιοποίηση υδροηλεκτρικών και συμβατικών μονάδων ηλεκτροπαραγωγής με χρήση μικτού ακέραιου γραμμικού προγραμματισμού», 4ο Εθνικό Συνέδριο «Η Εφαρμογή των Ανανεώσιμων Πηγών Ενέργειας», Αθήνα, 2010. download pdf