Subscription or Fee Access
A Cooperative Co-evolutionary Quantum Particle Swarm Optimizer based on Simulated Annealing for Job Shop Scheduling Problem
Job shop scheduling problem, a proved typical NP-hard problem, has been paid attention to and researchers have proposed various optimization algorithms. In this paper, a novel intelligent algorithm (SACQPSO) mixed with simulated annealing, cooperative co-evolution thought, quantum-behaved theory and particle swarm optimization algorithm is put forward, which could not only enhance the capacity of searching the best solution and increase the diversity of particles owing to co-operative co-evolution thought and quantum-behaved theory, but also strengthen the ability of global searching as the result of simulated annealing. Eventually, several typical JSSPs are solved effectively through SACQPSO, which is especially for problems on a large scale. The experimental results show that SACQPSO is more effective and feasible in comparison with PSO, QPSO, CPSO and CQPSO.
Simulated Annealing; Cooperative Co-evolutionary approach; Quantum-behaved Theory; Particle swarm optimization; Job Shop Scheduling Problem
Disclaimer/Regarding indexing issue:
We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.