Discrete event optimization: Workstation and buffer allocation problem in manufacturing flow lines

Zhang Mengyi, Andrea Matta, Giulia Pedrielli

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

12 Scopus citations


Resource and buffer allocation problems are well-known topics in manufacturing system research. A proper allocation of resource and space can significantly improve the system performance and reduce the investment cost. However, few works consider the joint problem because of its complexity. Recent research has shown that Discrete Event Optimization (DEO) framework, an integrated simulation-optimization approach based on mathematical programming, can be used to optimize buffer allocation of production lines, such as open and closed flow lines and pull controlled manufacturing systems. This paper proposes mathematical programming models for solving the joint workstation and buffer allocation problem in manufacturing flow lines constrained to a given target throughput. The problem is formulated in two different ways: An exact model using mixed integer linear programming formulation and approximate models using linear programming formulation. Numerical analysis shows that efficiency and accuracy can be both achieved by using approximate formulations in a math-heuristic procedure.

Original languageEnglish (US)
Title of host publication2016 Winter Simulation Conference
Subtitle of host publicationSimulating Complex Service Systems, WSC 2016
EditorsTheresa M. Roeder, Peter I. Frazier, Robert Szechtman, Enlu Zhou
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages12
ISBN (Electronic)9781509044863
StatePublished - Jul 2 2016
Event2016 Winter Simulation Conference, WSC 2016 - Arlington, United States
Duration: Dec 11 2016Dec 14 2016

Publication series

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


Other2016 Winter Simulation Conference, WSC 2016
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications


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