Efficient Algorithms for Flexible Job Shop Scheduling with Parallel Machines

Naval Research Logistics, 2020

45 Pages Posted: 21 Apr 2020

See all articles by Wieslaw Kubiak

Wieslaw Kubiak

University of Toronto

Yanling Feng

Beijing University of Posts and Telecommunications

Guo Li

University of Texas at Dallas; Beijing Institute of Technology

Suresh Sethi

University of Texas at Dallas - Naveen Jindal School of Management

Chelliah Sriskandarajah

Texas A&M University

Date Written: March 26, 2020

Abstract

Job shop scheduling with a bank of machines in parallel is important from both theoretical and practical points of review. Here we focus on a flexible job shop scheduling problem of minimizing the makespan in a two-center job shop, where the first center consists of one machine and the second consists of k parallel machines. We provide an easy-to-perform approximation algorithm that solves the problem optimally when k=1. A modification of the algorithm provides an optimal solution for k=2. For k≥3, the algorithm approximates the optimal solution within an absolute worst-case error bound of k−1. Surprisingly, this error bound is independent of the number of jobs to be processed. Also and importantly, the proposed algorithm runs in polynomial time and numerical experiments show its advantages in solving two-center flexible job shop problems.

Keywords: flexible job shop scheduling; makespan; approximation algorithm; absolute worst-case error bound

JEL Classification: C61, M11, M20

Suggested Citation

Kubiak, Wieslaw and Feng, Yanling and Li, Guo and Sethi, Suresh and Sriskandarajah, Chelliah, Efficient Algorithms for Flexible Job Shop Scheduling with Parallel Machines (March 26, 2020). Naval Research Logistics, 2020, Available at SSRN: https://ssrn.com/abstract=3561639

Wieslaw Kubiak

University of Toronto ( email )

105 St George Street
Toronto, Ontario M5S 3G8
Canada

Yanling Feng

Beijing University of Posts and Telecommunications

Guo Li

University of Texas at Dallas ( email )

2601 North Floyd Road
Richardson, TX 75083
United States

Beijing Institute of Technology ( email )

5 South Zhongguancun street
Center for Energy and Environmental Policy Researc
Beijing, Haidian District 100081
China

Suresh Sethi (Contact Author)

University of Texas at Dallas - Naveen Jindal School of Management ( email )

800 W. Campbell Road, SM30
Richardson, TX 75080-3021
United States

Chelliah Sriskandarajah

Texas A&M University ( email )

Langford Building A
798 Ross St.
77843-3137

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