Analysis of Integration Methods of Simulation, Evolutionary, and Expert Modeling to Optimize of Resource Conversion Processes

Abstract

An approach of the resource conversion processes as a model for formalization of the processes occurring in organizational and technical systems is considered. For analysis and optimization of such processes, simulation is widely used. The disadvantage of using computer modeling is the need to formulate such an experiment plan with the model that would contain an optimal control impact. This is impossible without using of additional heuristic or experiments planning methods. Analysis of hybrid heuristic methods for optimizing of the resource conversion processes is presented. These methods integrate simulation modeling and artificial intelligence methods, in particular expert systems, multi-agent and evolutionary modeling. Integration of simulation and heuristic methods for solving the problem considered is confirmed. Application of genetic algorithm for optimizing the controlled parameters of the simulation model or expert system is considered. A hybrid method of using the expert system for solving the problem of optimizing the operation of genetic algorithm is considered. Application of evolutionary modeling for centralized and decentralized coordination of agent behavior in multiagent systems is also considered. A hybrid heuristic method for solving the problem of forming various types of the agent's interactions in the multi-agent systems depending on the relationships of agents to common resources has been analyzed. Choice of the hybrid method for integrating multi-agent simulation and genetic algorithm for solving the problem of optimizing resource conversion processes is substantiated. This method is implemented in the multi-agent genetic optimization information technology in the BPsim. MAS dynamic situations modeling system and in the metallurgical enterprise information automated system.