Dual-objective mixed integer linear program and memetic algorithm for an industrial group scheduling problem

Ziyan Zhao, Shixin Liu, Meng Chu Zhou, Abdullah Abusorrah

Research output: Contribution to journalArticlepeer-review

Abstract

Group scheduling problems have attracted much attention owing to their many practical applications. This work proposes a new bi-objective serial-batch group scheduling problem considering the constraints of sequence-dependent setup time, release time, and due time. It is originated from an important industrial process, i.e., wire rod and bar rolling process in steel production systems. Two objective functions, i.e., the number of late jobs and total setup time, are minimized. A mixed integer linear program is established to describe the problem. To obtain its Pareto solutions, we present a memetic algorithm that integrates a population-based nondominated sorting genetic algorithm II and two single-solution-based improvement methods, i.e., an insertion-based local search and an iterated greedy algorithm. The computational results on extensive industrial data with the scale of a one-week schedule show that the proposed algorithm has great performance in solving the concerned problem and outperforms its peers. Its high accuracy and efficiency imply its great potential to be applied to solve industrial-size group scheduling problems.

Original languageEnglish (US)
JournalIEEE/CAA Journal of Automatica Sinica
DOIs
StateAccepted/In press - 2020

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Information Systems
  • Artificial Intelligence

Keywords

  • Job shop scheduling
  • Linear programming
  • Memetics
  • Single machine scheduling
  • Sorting
  • Steel
  • Task analysis

Fingerprint Dive into the research topics of 'Dual-objective mixed integer linear program and memetic algorithm for an industrial group scheduling problem'. Together they form a unique fingerprint.

Cite this