Name
Title | ||
|---|---|---|
A hybrid discrete particle swarm optimization for dual-resource constrained job shop scheduling with resource flexibility |
Abstract | ||
|---|---|---|
In this paper, a novel hybrid discrete particle swarm optimization algorithm is proposed to solve the dual-resource constrained job shop scheduling problem with resource flexibility. Particles are represented based on a three-dimension chromosome coding scheme of operation sequence and resources allocation. Firstly, a mixed population initialization method is used for the particles. Then a discrete particle swarm optimization is designed as the global search process by taking the dual-resources feature into account. Moreover, an improved simulated annealing with variable neighborhoods structure is introduced to improve the local searching ability for the proposed algorithm. Finally, experimental results are given to show the effectiveness of the proposed algorithm. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/s10845-015-1082-0 | J. Intelligent Manufacturing |
Keywords | Field | DocType |
Particle swarm optimization,Simulated annealing,Dual-resource constraint,Resource flexibility | Simulated annealing,Particle swarm optimization,Population,Mathematical optimization,Job shop scheduling,Multi-swarm optimization,Coding (social sciences),Artificial intelligence,Initialization,Engineering,Machine learning,Metaheuristic | Journal |
Volume | Issue | ISSN |
28 | 8 | 0956-5515 |
Citations | PageRank | References |
6 | 0.47 | 17 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jing Zhang | 1 | 12 | 1.95 |
| Wan-Liang Wang | 2 | 235 | 39.16 |
| Xinli Xu | 3 | 79 | 10.92 |