Study of stochastic sequence-dependent flexible flow shop via developing a dispatching rule and a hybrid GA

  • Authors:
  • K. Kianfar;S. M. T. Fatemi Ghomi;A. Oroojlooy Jadid

  • Affiliations:
  • Department of Industrial Engineering, Isfahan University of Technology, Isfahan, Iran;Department of Industrial Engineering, Amirkabir University of Technology, 424 Hafez Avenue, Tehran, Iran;Department of Industrial Engineering, Sharif University of Technology, Azadi Avenue, Tehran, Iran

  • Venue:
  • Engineering Applications of Artificial Intelligence
  • Year:
  • 2012

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Abstract

A flexible flow shop is a generalized flow shop with multiple machines in some stages. This system is fairly common in flexible manufacturing and in process industry. In most practical environments, scheduling is an ongoing reactive process where the presence of real time information continually forces reconsideration of pre-established schedules. This paper studies a flexible flow shop system considering non-deterministic and dynamic arrival of jobs and also sequence dependent setup times. The problem objective is to determine a schedule that minimizes average tardiness of jobs. Since the problem class is NP-hard, a novel dispatching rule and hybrid genetic algorithm have been developed to solve the problem approximately. Moreover, a discrete event simulation model of the problem is developed for the purpose of experimentation. The most commonly used dispatching rules from the literature and two new methods presented in this paper are incorporated in the simulation model. Simulation experiments have been conducted under various experimental conditions characterized by factors such as shop utilization, setup time level and number of stages. The results indicate that methods proposed in this study are much better than the traditional dispatching rules.