A PROBABILITY-DRIVEN SEARCH ALGORITHM FOR SOLVING MULTI-OBJECTIVE OPTIMIZATION PROBLEMS
Nguyen Huu Thong (thong_nh2002yahoo.com)
Abstract: This paper proposes a new probabilistic algorithm for solving multi-objective optimization problems - Probability-Driven Search Algorithm. The algorithm uses probabilities to control the process in search of Pareto optimal solutions. Especially, we use the absorbing Markov Chain to argue the convergence of the algorithm. We test this approach by implementing the algorithm on some benchmark multi-objective optimization problems, and find very good and stable results.
Keywords: multi-objective, optimization, stochastic, probability, algorithm.
Category 1: Other Topics (Multi-Criteria Optimization )
Category 2: Global Optimization (Stochastic Approaches )
Category 3: Nonlinear Optimization
Citation: Thong Nguyen Huu and Hao Tran Van, A probability-driven search algorithm for solving multi-objective optimization problems, Journal of science, Special issue: Natural sciences and technology, Ho Chi Minh city University of Education, 33(67), 2012.
Entry Submitted: 01/30/2012
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