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A method for mixed integer programming problems by particle swarm optimization
Author(s) -
Kitayama Satoshi,
Yasuda Keiichiro
Publication year - 2006
Publication title -
electrical engineering in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.136
H-Index - 28
eISSN - 1520-6416
pISSN - 0424-7760
DOI - 10.1002/eej.20337
Subject(s) - penalty method , mathematical optimization , particle swarm optimization , nonlinear programming , integer programming , continuous optimization , discrete optimization , integer (computer science) , optimization problem , multi swarm optimization , function (biology) , mathematics , linear programming , variable (mathematics) , computer science , nonlinear system , mathematical analysis , physics , quantum mechanics , evolutionary biology , biology , programming language
Particle Swarm Optimization (PSO) for mixed integer programming problems is proposed. PSO is mainly a method to find a global or quasi‐minimum for a nonlinear and nonconvex optimization problem, and there have been few studies into optimization problems with discrete decision variables. In this paper, we present the treatment of discrete variables. To treat discrete decision variables as a penalty function, it is possible to treat all decision variables as a continuous decision variable. As a result, the penalty parameter for the penalty function is needed. In this paper, we also present how to determine the penalty parameter for the penalty function. Through mathematical and structural optimization problems, we examine the validity of PSO for the mixed decision variables. © 2006 Wiley Periodicals, Inc. Electr Eng Jpn, 157(2): 40–49, 2006; Published onlinein Wiley InterScience www.interscience.wiley.com ). DOI 10.1002/eej.20337