Integrated model for the batch sequencing problem in a multi-stage supply chain: An artificial immune system based approach

M. Shukla, N. Shukla, M. K. Tiwari, Tung Sun Chan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

13 Citations (Scopus)

Abstract

In this paper a mathematical model for the batch sequencing problem in a multistage supply chain is developed by taking into account three practically important objectives, viz. minimization of lead time, blocking time and due date violation. Attribute dependent operation time, sequence dependent setup time, different due dates, different lot sizes for batches and variable time losses due to interaction among several stages like waiting, idling, and blocking are also considered in the model. The problem is combinatorial in nature and complete enumeration of all its possibilities is computationally prohibitive. Therefore, a metaheuristic, artificial immune system (AIS) is employed to find an optimal/near optimal solution. In order to test the efficacy of AIS in solving the problem, its implementation on four different problems has been studied. Further, the comparative analysis of the results obtained by implementing AIS, genetic algorithm (GA) and simulated annealing (SA) on the proposed model reveals that AIS outperforms GA and SA in solving the underlying problem.
Original languageEnglish
Pages (from-to)1015-1037
Number of pages23
JournalInternational Journal of Production Research
Volume47
Issue number4
DOIs
Publication statusPublished - 1 Jan 2009
Externally publishedYes

Keywords

  • Artificial immune system (AIS)
  • Lead time
  • Multistage supply chain

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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