An efficient job-shop scheduling algorithm based on particle swarm optimization

作者：Lin Tsung Lieh; Horng Shi Jinn^*; Kao Tzong Wann; Chen Yuan Hsin; Run Ray Shine; Chen Rong Jian; Lai Jui Lin; Kuo I Hong

来源：Expert Systems with Applications, 2010, 37(3): 2629-2636.

DOI：10.1016/j.eswa.2009.08.015

• Job-shop scheduling problem
• Particle swarm optimization
• Multi-type individual enhancement scheme
• Random-key encoding scheme
• Simulated annealing

The job-shop scheduling problem has attracted many researchers' attention in the past few decades, and many algorithms based on heuristic algorithms, genetic algorithms, and particle swarm optimization algorithms have been presented to solve it, respectively. Unfortunately, their results have not been satisfied at all yet. In this paper, a new hybrid swarm intelligence algorithm consists of particle swarm optimization, simulated annealing technique and multi-type individual enhancement scheme is presented to solve the job-shop scheduling problem. The experimental results show that the new proposed job-shop scheduling algorithm is more robust and efficient than the existing algorithms.

• 出版日期2010-3-15