This volume gathers selected, peer-reviewed works presented at the 7th International Conference on Optimization, Simulation and Control, ICOSC 2022, held at the National University of Mongolia, Ulaanbaatar, June 2022, 2022. Topics covered include (but are not limited to) mathematical programming; network, global, linear, nonlinear, parametric, stochastic, and multi-objective optimization; control theory; biomathematics; and deep and machine learning, to name a few. Held every three years since 2002, the ICOSC conference has become a traditional gathering for experienced and young researchers in optimization and control to share recent findings in these fields and discuss novel applications in myriad sectors. Researchers and graduate students in the fields of mathematics, engineering, and computer science can greatly benefit from this book, which can also be enjoyed by advanced practitioners in research laboratories and the industry. The 2022 edition of the ICOSC conference was sponsored by the Mongolian Academy of Sciences, the National University of Mongolia and the German-Mongolian Institute for Resources and Technology.

Gathers recent findings in optimization and control, with myriad applications Includes studies on network, global, nonlinear, stochastic, and multi-objective optimization Of interest to researchers and advanced practitioners alike

Autorentext

Rentsen Enkhbat is a Professor at the National University of Mongolia. He is also the head of the Mathematical department in the Institute of Mathematics and Digital Technology of the Mongolian Academy of Sciences. He received his Ph.D from the Irkutsk State University, Russia in 1990 and Sc.D. from the Mongolian Academy of Sciences in 2002. His research focuses on global optimization, game theory and optimal control.
Altannar Chinchuluun is a faculty member of the Business School at the National University of Mongolia. He is also a researcher at the Institute of Mathematics and Digital Technology of the Mongolian Academy of Sciences. He received his Ph.D from the University of Florida in 2007. His research focuses on optimization, network design problems, data mining with biomedical applications and computational finance.

Panos M. Pardalos is an Emeritus Professor in the Industrial and Systems Engineering at the University of Florida. He received his Ph.D. from the University of Minnesota in 1985. ** Additionally, he is the Paul and Heidi Brown Preeminent Professor of Industrial and Systems Engineering at the University of Florida. He is also an affiliated faculty member of the Computer and Information Science Department, the Hellenic Studies Center, and the biomedical engineering program at the University of Florida. He is also the director of the Center for Applied Optimization at the University of Florida. He is a world leading expert in global and combinatorial optimization. His research interests include network design problems, optimization in telecommunications, e-commerce, data mining, biomedical applications, and massive computing.

Inhalt
Covering Balls and HT -differential for Convex Maximizaton.- Employing the Cloud for finding Solutions to Large Systems of Nonlinear Equations.- An Approximation Scheme for a Bilevel Knapsack Problem.- Efficient heuristics for a partial set covering problem with mutually exclusive pairs of facilities.- A Hybrid Genetic Algorithm For The Budget-constrained Charging Station Location Problem.- Optimal Advertising Expenditure.- Pre-clustered Generative Adversarial Network Model for Mongolian Font Style Transfer.- Designing information sharing platform using IoT and AI for Farming Management System.- Monowave Boundary Construction Method for the Non-convex Reachable Set of the Controlled Dynamical System.- Storage Reduction of Forward-Backward Sweeping Method of Optimal Control of Active Queue Management.- Extremal Controls Searching Methods Based on Fixed Point Problems.- The Globalized Modification of Rosenbrock Algorithm for Finding Anti-Nash Equilibrium in Bimatrix Game.-Optimal Choice of Parameters in Higher-Order Derivative-Free Iterative Methods for Systems of Nonlinear Equations.- Extending Nonstandard Finite Difference Scheme for SIR Epidemic Model.