A modified shifting bottleneck heuristic for the reentrant job shop scheduling problem with makespan minimization


Topaloglu Ş. A., Kilincli G.

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, cilt.44, sa.7-8, ss.781-794, 2009 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 44 Sayı: 7-8
  • Basım Tarihi: 2009
  • Doi Numarası: 10.1007/s00170-008-1881-y
  • Dergi Adı: INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.781-794
  • Anahtar Kelimeler: Reentrant job shop scheduling problem, Shifting bottleneck heuristic, Makespan minimization, Single-machine maximum lateness problem, TOTAL WEIGHTED TARDINESS, INTEGER PROGRAMMING FORMULATIONS, SUBPROBLEM SOLUTION PROCEDURES, ALGORITHM
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

This paper proposes a modified shifting bottleneck heuristic (MSBH) for the reentrant job shop scheduling problem (RJSSP) with makespan minimization objective. Recently, the reentrant job shop has come into prominence as a new type of manufacturing shop. The principle characteristic of a reentrant job shop is that a job may visit certain machines more than once during the process flow, whereas in the classic job shop, each job visits a machine only once. The shifting bottleneck heuristic (SBH) is one of the most successful heuristic approaches for the classical job shop scheduling problem, which decomposes the problem into a number of single-machine subproblems. This paper adapts the SBH for the RJSSP and proposes a new sequencing heuristic for the single-machine maximum lateness subproblem considering the reentrant jobs in order to handle large-size RJSSPs. It also uses a subproblem criticality measure that further shortens the implementation time. The proposed MSBH is tested by using instances up to 20 machines and 100 jobs, and it is illustrated that good quality solutions can be obtained in reasonable computational times. A real-life application of the MSBH is also given as a case study to evaluate its performance.