An Efficient Relax-and-Solve Heuristic for Open-Shop Scheduling Problem to Minimize Total Weighted Earliness-Tardiness

18 Pages Posted: 9 Jun 2020

See all articles by Mohammad Mahdi Ahmadian

Mohammad Mahdi Ahmadian

University of Technology Sydney (UTS)

Amir Salehipour

University of Technology Sydney, Australia; University of Technology Sydney (UTS)

Mikhail Kovalyov

United Institute of Informatics Problems

Date Written: May 14, 2020

Abstract

An open-shop scheduling problem to minimize the total weighted earliness-tardiness of job-on-machine operations is studied. Each operation has its own due date, earliness weight and tardiness weight. An efficient relax-and-solve heuristic is developed. A feature that makes the proposed heuristic distinctive from the existing heuristics of this kind is that it operates by iterative relaxation and optimization of a series of sub-problems. Performance of the proposed heuristic is verified on a set of 72 benchmark instances with up to 200 operations, adapted from the literature on a similar job-shop scheduling problem. The heuristic delivers best solutions for nearly 71\% of the instances (i.e., 51 out of 72 instances), including the best solution for all instances with 150 and 200 operations. Its running time is around three minutes, while CLPEX was run for 30 minutes.

Keywords: open-shop scheduling, just-in-time, weighted earliness-tardiness, relaxation neighborhood, matheuristic, relax-and-solve

Suggested Citation

Ahmadian, Mohammad Mahdi and Salehipour, Amir and Salehipour, Amir and Kovalyov, Mikhail, An Efficient Relax-and-Solve Heuristic for Open-Shop Scheduling Problem to Minimize Total Weighted Earliness-Tardiness (May 14, 2020). Available at SSRN: https://ssrn.com/abstract=3601396 or http://dx.doi.org/10.2139/ssrn.3601396

Mohammad Mahdi Ahmadian

University of Technology Sydney (UTS) ( email )

15 Broadway, Ultimo
PO Box 123
Sydney, NSW 2007
Australia

Amir Salehipour (Contact Author)

University of Technology Sydney, Australia ( email )

Ultimo
Ultimo, NSW 2007
Australia

University of Technology Sydney (UTS) ( email )

15 Broadway, Ultimo
PO Box 123
Sydney, NSW 2007
Australia

Mikhail Kovalyov

United Institute of Informatics Problems ( email )

Minsk
Belarus

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
120
Abstract Views
562
Rank
419,528
PlumX Metrics