Heuristics for Order-Lot Pegging in Multi-Fab Settings

Lars Monch, Liji Shen, John W. Fowler

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we study order-lot pegging problems in semiconductor supply chains. The problem deals with assigning already released lots to orders and with planning wafer releases to fulfill orders if there are not enough lots. The objective is to minimize the total tardiness of the orders. We propose a mixed integer linear programming (MILP) formulation for this problem. Moreover, we design a simple heuristic based on list scheduling and a biased random key genetic algorithm (BRKGA). Computational experiments based on problem instances from the literature for the single-fab case and newly proposed instances for the multi-fab setting are conducted. The results demonstrate that the BRKGA approach is able to determine high-quality solutions in a short amount of computing time.

Original languageEnglish (US)
Title of host publicationProceedings of the 2020 Winter Simulation Conference, WSC 2020
EditorsK.-H. Bae, B. Feng, S. Kim, S. Lazarova-Molnar, Z. Zheng, T. Roeder, R. Thiesing
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1742-1752
Number of pages11
ISBN (Electronic)9781728194998
DOIs
StatePublished - Dec 14 2020
Event2020 Winter Simulation Conference, WSC 2020 - Orlando, United States
Duration: Dec 14 2020Dec 18 2020

Publication series

NameProceedings - Winter Simulation Conference
Volume2020-December
ISSN (Print)0891-7736

Conference

Conference2020 Winter Simulation Conference, WSC 2020
Country/TerritoryUnited States
CityOrlando
Period12/14/2012/18/20

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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