Journal
THEORY, METHODOLOGY, TOOLS AND APPLICATIONS FOR MODELING AND SIMULATION OF COMPLEX SYSTEMS, PT II
Volume 644, Issue -, Pages 71-78Publisher
SPRINGER-VERLAG SINGAPORE PTE LTD
DOI: 10.1007/978-981-10-2666-9_8
Keywords
shop scheduling problem; Particle swarm optimization; Simulated annealing; Maximum completion time
Funding
- Aviation Science Fund of China [20141625003]
Ask authors/readers for more resources
This paper proposes a new hybrid PSO optimization algorithm, which fuses GA and simulated annealing (SA) into the PSO algorithm. The crossover and mutation mechanism of GA algorithm make the new hybrid algorithm keep the diversity of population and retain the good factors in the population to jump out of local optimum. The sudden jump probability of SA also guarantees the diversity of the population, thus preventing local minimum of the hybrid PSO algorithm. This new hybrid algorithm is used to minimize the maximum completion time of the scheduling problems. The simulation results show that the performance of hybrid optimization algorithm outperforms another hybrid PSO algorithm. The hybrid PSO algorithm is not only in the structure of the algorithm, but also the search mechanism provides a powerful way to solve JSSP.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available