Effective algorithm designed for solving multi-objective optimization problems
Cao De-xin · Journal of Heilongjiang Institute of Science and Technology · 2010
In order to overcome the limitations of existing methods used for solving multi-objective optimization problems,this paper proposes a new global convergent algorithm—Adjustable Entropy Interval Algorithm for a class of constrained multi-objective optimization problems in which the objective functions and constrained conditions are C1.The paper introduces the practices of changing the constrained multi-objective optimization problems into unconstrained,combined with the idea point methods and adjustable entropy principle and then developing the Adjustable Entropy Interval Algorithm by constructing the interval extension of the objection function and region deletion testing rules and proves the convergence of algorithm.Numerical results of many typical test functions show that the algorithm is effective and reliable.