Volume 29, Issue 2 (IJIEPR 2018)                   IJIEPR 2018, 29(2): 197-211 | Back to browse issues page


XML Print


1- University of Science and Technology of Mazandaran
2- University of Science and Technology of Mazandaran , mostafahaji@mazust.ac.ir
Abstract:   (592 Views)

Nowadays, several methods in production management mainly focus on the different partners of supply chain management. In real world, the capacity of planes is limited. In addition, the recent decade has seen the rapid development of controlling the uncertainty in the production scheduling configurations along with proposing novel solution approaches. This paper proposes a new mathematical model via strong recent meta-heuristics planning. This study firstly develops and coordinates the integrated air transportation and production scheduling problem with time windows and due date time in Fuzzy environment to minimize the total cost. Since the problem is NP-hard, we use four meta-heuristics along with some new procedures and operators to solve the problem. The algorithms are divided into two groups: traditional and recent ones. Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) as traditional algorithms, also Keshtel Algorithm (KA) and Virus Colony Search (VCS) as the recent ones are utilized in this study. In addition, by using Taguchi experimental design, the algorithm parameters are tuned. Besides, to study the behavior of the algorithms, different problem sizes are generated and the results are compared and discussed.

Full-Text [PDF 828 kb]   (211 Downloads)    
Highlights:
  • Proposing a mathematical model for an integrated air transportation and production scheduling problem under fuzzy considerations;
  • Introducing two recent metaheuristics called Keshtel Algorithm (KA) and Virus Colony Search (VCS);
  • Confirming the performance of KA and efficiency of proposed model through a set of analyses

Type of Study: Research | Subject: Logistic & Apply Chain
Received: 2017/04/11 | Accepted: 2018/05/20 | Published: 2018/05/20