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Abstract

The Workload Allocation Problem consists of assigning a sequence of (Formula presented.) operations to workers. The order of these operations is fixed. Each operation consists of a batch of B units, hence a total of (Formula presented.) jobs have to be performed. Each worker is assigned to an ordered subset of consecutive jobs. Workers have different skills, and therefore jobs take a variable time to process, depending on the assigned worker. The study of this problem is rooted in the operations of Calzedonia. In this paper, we briefly introduce the application before presenting algorithms for solving the problem exactly and heuristically. Our computational results compare the performance of a stand-alone mathematical formulation solved by CPLEX, a sequential exact algorithm, and a metaheuristic, with a simple heuristic implemented in the company.

Original languageEnglish
Pages (from-to)2004-2017
Number of pages14
JournalJournal of the Operational Research Society
Volume72
Issue number9
Early online date23 Jun 2020
DOIs
Publication statusPublished - 31 Dec 2021

Bibliographical note

Funding Information:
This work was partially supported by the Canadian Natural Sciences and Engineering Research Council under grant 2015-06189. This support is gratefully acknowledged. This research made use of the Balena High Performance Computing (HPC) Service at the University of Bath. Thanks are due to the referees for their valuable comments.

Funding Information:
This work was partially supported by the Canadian Natural Sciences and Engineering Research Council under grant 2015-06189. This support is gratefully acknowledged. This research made use of the Balena High Performance Computing (HPC) Service at the University of Bath. Thanks are due to the referees for their valuable comments.

Publisher Copyright:
© Operational Research Society 2020.

Keywords

  • Combinatorial optimisation
  • production
  • scheduling

ASJC Scopus subject areas

  • Modelling and Simulation
  • Strategy and Management
  • Statistics, Probability and Uncertainty
  • Management Science and Operations Research

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