Mathematical models for job-shop scheduling problems with routing and process plan flexibility

Ozguven C., ÖZBAKIR L., YAVUZ Y.

APPLIED MATHEMATICAL MODELLING, vol.34, no.6, pp.1539-1548, 2010 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 34 Issue: 6
  • Publication Date: 2010
  • Doi Number: 10.1016/j.apm.2009.09.002
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1539-1548
  • Keywords: Job-shop scheduling, Routing flexibility, Process plan flexibility, Mixed-integer programming, TABU SEARCH, GENETIC ALGORITHM, ENVIRONMENT, INTEGRATION, OPERATION
  • Erciyes University Affiliated: Yes


As a result of rapid developments in production technologies in recent years, flexible job-shop scheduling problems have become increasingly significant. This paper deals with two NP-hard optimization problems: flexible job-shop scheduling problems (FJSPs) that encompass routing and sequencing sub-problems, and the FJSPs with process plan flexibility (FJSP-PPFs) that additionally include the process plan selection sub-problem. The study is carried out in two steps. In the first step, a mixed-integer linear programming model (MILP-1) is developed for FJSPs and compared to an alternative model in the literature (Model F) in terms of computational efficiency. In the second step, one other mixed-integer linear programming model, a modification of MILP-1, for the FJSP-PPFs is presented along with its computational results on hypothetically generated test problems. (C) 2009 Elsevier Inc. All rights reserved.