Title :
An Improved PSO Algorithm for Resource-Constrained Project Scheduling Problem
Author :
Xinggang Luo ; Dingwei Wang ; Jiafu Tang ; Yiliu Tu
Author_Institution :
Comput. Center, Northeastern Univ., Shenyang
Abstract :
An improved particle swarm optimization (PSO) algorithm for resource-constrained project scheduling problem is proposed. The particle presentation, encoding scheme and decoding rule of this algorithm are presented. Improvements based on the basic PSO include: the particle swarm is initialized by heuristic rule to improve the quality of particles; inertia weight is self-adapted with iteration of the algorithm to decelerate the speed of particles; crossover mechanism of genetic algorithm are applied to particle swarm to enable the exchange of good characteristics between two particles. Computational results for project instances of PSPLIB demonstrate that this improved PSO is effective compared with other mataheuristic approaches
Keywords :
particle swarm optimisation; scheduling; crossover mechanism; decoding rule; encoding scheme; genetic algorithm; heuristic rule; inertia weight; particle presentation; particle swarm optimization; resource-constrained project scheduling problem; Computer aided manufacturing; Encoding; Genetic algorithms; Information science; Intelligent control; Iterative decoding; Job shop scheduling; Particle swarm optimization; Processor scheduling; Scheduling algorithm; particle swarm optimization; project scheduling; resource-constrained;
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1713022
