Modeling and heuristics for production time crashing in supply chain network design

Yi Liao, Ali Diabat, Chaher Alzaman, Yiqiang Zhang

Research output: Contribution to journalArticlepeer-review


Supply chains with shorter lead times can bring their constituents cost reductions, flexibility, and speed. Since manufacturing is a prominent operation within the supply chain, the reduction of its time duration can prove important in reducing the overall supply chain’s lead-time. Some works in the area of supply chain network design (SCND) have looked at the crashing of supply chain’s lead-time. However, the literature lacks works that explicitly model a crashing cost in SCND. The work formulates a cost model that integrates production, crashing, inventory, transportation, and plant selection. Given the complexity of these elements, the model emerging is a nonlinear and binary in both the objective function and the constraints. The paper introduces a gradient search method to solve the model coupled with efficient search heuristics. The work presents seven search heuristics along with variants to solve the difficult problem at hand. Further, the work looks at different parameters that affect the crashing cost, presents the cost avoidances that can result from crashing, and discusses the operational opportunities to be reaped.

Original languageEnglish (US)
Pages (from-to)331-361
Number of pages31
JournalAnnals of Operations Research
Issue number1
StatePublished - May 1 2020


  • Gradient search
  • Local search heuristic
  • Manufacturing
  • Nonlinear mixed integer programming
  • Resource allocation
  • Supply chain network design

ASJC Scopus subject areas

  • General Decision Sciences
  • Management Science and Operations Research


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