Parallel multi-population Particle Swarm Optimization Algorithm for the Uncapacitated Facility Location problem using OpenMP
- Resource Type
- Conference
- Authors
- Dazhi Wang; Chun-Ho Wu; Ip, Andrew; Dingwei Wang; Yang Yan
- Source
- 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence) Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on. :1214-1218 Jun, 2008
- Subject
- Computing and Processing
Evolutionary computation
Equations
Organizations
Mathematical model
Manganese
Next generation networking
- Language
- ISSN
- 1089-778X
1941-0026
Parallel multi-population Particle Swarm Optimization (PSO) Algorithm using OpenMP is presented for the Uncapacitated Facility Location (UFL) problem. The parallel algorithm performed asynchronously by dividing the whole particle swarm into several sub-swarms and updated the particle velocity with a variety of local optima. Each sub-swarm changes its best position so far of to its neighbor swarm after certain generations. The parallel multi-population PSO (PMPSO) algorithm is applied to several benchmark suits collected from OR-library. And the results are presented and compared to the result of serial execution multi-population PSO. It is conducted that the parallel multi-population PSO is time saving, especially for large scale problem and generated more robust results.