Two New Meta-Model Based Artificial Neural Network Algorithms for Constrained Simulation Optimization Problems with Stochastic Constraints, M.Sc. Thesis Sharif University of Technology ; Mahlooji, Hashem (Supervisor)
Abstract
Following the recent developments in the field of decision making, a considerable number of problems involved with stochastic systems can be thought of whose analysis depends on a set of intricate mathematical relations. In such cases, simulation is one of the most popular tools that can be applied toward analysis of behavior of such stochastic systems. Not only does not the simulation model rely on such intricate mathematical relations, it also enjoys the added advantage of being free of any restricting assumptions which may normally be considered in a stochastic system.To analyze such problem, one may aim at determining the best combination of input variables to optimize the system...
Cataloging briefTwo New Meta-Model Based Artificial Neural Network Algorithms for Constrained Simulation Optimization Problems with Stochastic Constraints, M.Sc. Thesis Sharif University of Technology ; Mahlooji, Hashem (Supervisor)
Abstract
Following the recent developments in the field of decision making, a considerable number of problems involved with stochastic systems can be thought of whose analysis depends on a set of intricate mathematical relations. In such cases, simulation is one of the most popular tools that can be applied toward analysis of behavior of such stochastic systems. Not only does not the simulation model rely on such intricate mathematical relations, it also enjoys the added advantage of being free of any restricting assumptions which may normally be considered in a stochastic system.To analyze such problem, one may aim at determining the best combination of input variables to optimize the system...
Find in contentBookmark |
|