Title :
A Modified Binary Particle Swarm Optimization Algorithm for Permutation Flow Shop Problem
Author :
Yuan, Lei ; Zhao, Zhen-Dong
Author_Institution :
Nanjing Univ. of Posts & Telecommun., Nanjing
Abstract :
In this paper, we proposed a modified version of binary particle swarm optimization algorithm (MBPSO) to solve combinatorial optimization problems. All particles are initialized as random binary vectors, and the Smallest Position Value (SPV) rule is used to construct a mapping from binary space to the permutation space. We also propose new formula to update the particles´ velocities and positions. The algorithm is then applied to the permutation flow shop problem (PFSP). To avoid the stagnation, local search and perturbation are employed to improve the performance. Performance of the proposed algorithm is evaluated using the benchmarks of flow shop scheduling problems given by Taillard, (1993). Experimental results show that the algorithm with local search and perturbation is more effective.
Keywords :
combinatorial mathematics; flow shop scheduling; particle swarm optimisation; random processes; vectors; binary space; combinatorial optimization problems; flow shop scheduling problems; modified binary particle swarm optimization algorithm; permutation flow shop problem; permutation space; random binary vectors; smallest position value rule; Cybernetics; Dynamic programming; Electronic mail; Evolutionary computation; Job shop scheduling; Machine learning; Machine learning algorithms; Optimal scheduling; Particle swarm optimization; Scheduling algorithm; Binary particle swarm optimization; Flow shop problem; Local search; Perturbation; SPV rule;
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
DOI :
10.1109/ICMLC.2007.4370270