Multi-Objective Optimization Algorithm Based on Game Theory and Its Application in Scheduling of Real-Time Tasks
Lin Chen1,2, Xianjia Wang1,3
COMPUTER MODELLING & NEW TECHNOLOGIES 2014 18(12C) 645-649
1 Institute of Systems Engineering, Wuhan University, Wuhan, 430072, China
2 School of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan, 430081, China
3 School of Economics and Management, Wuhan University, Wuhan, 430072, China
Biological through survival of the fittest competition, to optimize today’s nature. Optimization is an effective way to draw inspiration from the natural evolution of human beings to solve its difficulties; it provides a general framework for solving complex optimization problems. And compared with the game theory demands completely rational assumption, game is on the premise of limited rational optimization algorithm, the game parties by repeating the game in the process of learning, imitation, competition, finding a good strategy, improve their own interests, finally the structure is achieve a dynamic balance on the basis of the optimization algorithm of game theory, this paper studied the production scheduling problem based on evolutionary game. First outlined the game related theory, optimization algorithm and multi-objective optimization algorithm for a class of real-time task scheduling problem, the corresponding evolutionary game model is established, using heuristic genetic algorithm to obtain the corresponding equilibrium solution, using multi-objective optimization algorithm is demonstrated by the simulation results of game theory to solve production scheduling problem is a good idea and has a broad development prospects.