کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
385396 | 660865 | 2011 | 9 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Handling multi-objective optimization problems with a multi-swarm cooperative particle swarm optimizer Handling multi-objective optimization problems with a multi-swarm cooperative particle swarm optimizer](/preview/png/385396.png)
This paper presents a new multi-objective optimization algorithm in which multi-swarm cooperative strategy is incorporated into particle swarm optimization algorithm, called multi-swarm cooperative multi-objective particle swarm optimizer (MC-MOPSO). This algorithm consists of multiple slave swarms and one master swarm. Each slave swarm is designed to optimize one objective function of the multi-objective problem in order to find out all the non-dominated optima of this objective function. In order to produce a well distributed Pareto front, the master swarm is developed to cover gaps among non-dominated optima by using a local MOPSO algorithm. Moreover, in order to strengthen the capability locating multiple optima of the PSO, several improved techniques such as the Pareto dominance-based species technique and the escape strategy of mature species are introduced. The simulation results indicate that our algorithm is highly competitive to solving the multi-objective optimization problems.
► A MOPSO algorithm based on multi-swarms cooperative strategy is presented.
► This algorithm consists of multiple slave swarms and one master swarm.
► Non-dominated optima of each objective function will be found by the slave swarms.
► Gaps among non-dominated optima will be covered by the master swarm.
► The proposed algorithm shows good performance to solving the MOPs.
Journal: Expert Systems with Applications - Volume 38, Issue 11, October 2011, Pages 13933–13941