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A two-criteria objective function flexible flowshop scheduling problem with machine eligibility constraint

Tadayon, B ; Sharif University of Technology | 2013

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  1. Type of Document: Article
  2. DOI: 10.1007/s00170-012-4052-0
  3. Publisher: 2013
  4. Abstract:
  5. This research deals with a flexible flowshop scheduling problem with the arrival and delivery of jobs in groups and processing them individually. Each group of jobs has a specific release time. Due to the special characteristics of each job, only a specific group of machines in each stage are eligible to process that job. All jobs in a group should be delivered at the same time after processing. The objectives of the problem are the minimization of the sum of the completion time of groups on one hand and the minimization of sum of the differences between the completion time of jobs and the delivery time of the group containing that job (waiting period) on the other hand. The problem can be stated as FFc /r j, M j /irreg based on existing scheduling notations. This problem has many applications in the production and service industries such as ceramic tile manufacturing companies and restaurants. A mathematical model has been proposed to solve the problem. Since the research problem is shown to be NP-complete, a particle swarm optimization (PSO) algorithm is applied to solve the problem approximately. Based on the frequency of using local search procedure, four scenarios of PSO have been developed. The algorithms are compared by applying experimental design techniques on random test problems with different sizes. The results show that the PSO algorithm enhanced with local search for all particles has a weaker performance than the other scenarios in solving large-sized problems
  6. Keywords:
  7. Flexible flowshop scheduling ; Mathematical modeling ; A-particles ; Ceramic tile ; Completion time ; Delivery time ; Different sizes ; Experimental design techniques ; Flexible flowshop ; Group processing ; Large-sized ; Local search ; Machine eligibility constraint ; NP Complete ; Objective functions ; PSO algorithms ; Random tests ; Release time ; Research problems ; Service industries ; Algorithms ; Mathematical models ; Particle swarm optimization (PSO) ; Scheduling ; Problem solving
  8. Source: International Journal of Advanced Manufacturing Technology ; Volume 64, Issue 5-8 , April , 2013 , Pages 1001-1015 ; 02683768 (ISSN)
  9. URL: http://link.springer.com/article/10.1007%2Fs00170-012-4052-0