A GEP-based reactive scheduling policies constructing approach for dynamic flexible job shop scheduling problem with job release dates

  • Authors:

  • Li Nie;Liang Gao;Peigen Li;Xinyu Li

  • Affiliations:

  • School of Mechanical and Electronic Engineering, Shanghai Second Polytechnic University, Pudong District, Shanghai, People's Republic of China 201209 and The State Key Laboratory of Digital Manufa ...;The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China 430074;The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China 430074;The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China 430074

  • Venue:
  • Journal of Intelligent Manufacturing
  • Year:
  • 2013

Quantified Score

Hi-index 0.00

Visualization

Abstract

Flexible job shop scheduling problem (FJSSP) is generalization of job shop scheduling problem (JSSP), in which an operation may be processed on more than one machine each of which has the same function. Most previous researches on FJSSP assumed that all jobs to be processed are available at the beginning of scheduling horizon. The assumption, however, is always violated in practical industries because jobs usually arrive over time and can not be predicted before their arrivals. In the paper, dynamic flexible job shop scheduling problem (DFJSSP) with job release dates is studied. A heuristic is proposed to implement reactive scheduling for the dynamic scheduling problem. An approach based on gene expression programming (GEP) is also proposed which automatically constructs reactive scheduling policies for the dynamic scheduling. In order to evaluate the performance of the reactive scheduling policies constructed by the proposed GEP-based approach under a variety of processing conditions three factors, such as the shop utilization, due date tightness, problem flexibility, are considered in the simulation experiments. The scheduling performance measure considered in the simulation is the minimization of makespan, mean flowtime and mean tardiness, respectively. The results show that GEP-based approach can construct more efficient reactive scheduling policies for DFJSSP with job release dates under a big range of processing conditions and performance measures in the comparison with previous approaches.