A scheduling model for the refurbishing process in recycling management

Edwin Tai Chiu Cheng, B. M.T. Lin, Y. Tian

Research output: Journal article publicationReview articleAcademic researchpeer-review

4 Citations (Scopus)

Abstract

We propose from the perspective of operations scheduling a novel model of the refurbishing process in recycling management. We model the refurbishing process as a two-stage flowshop that dismantles products into parts in stage one and refurbishes the parts on dedicated machines in stage two. The model also features that the performance measure of a schedule is defined by operation-based completion times, which is different from the job-based performance measures traditionally adopted in the scheduling literature. We analyse the optimality properties and computational complexity of some special cases of the problem. We derive lower bounds on the optimal solution based on a disaggregation technique and the assignment problem, and develop dominance rules incorporating estimates of the effects of partial schedules on unscheduled jobs. We present a heuristic approach, based on LP relaxation, and analyse its performance ratio. We also develop two metaheuristic algorithms, based on iterated local search and ant colony optimisation, to produce approximate solutions. The results of computational experiments show that the metaheuristics generate better solutions than the simple weighted shortest processing time dispatching rule, and the NEH-based and CDS-based algorithms, which are commonly deployed to treat the classical two-machine flowshop scheduling problem.
Original languageEnglish
Pages (from-to)7120-7139
Number of pages20
JournalInternational Journal of Production Research
Volume51
Issue number23-24
DOIs
Publication statusPublished - 1 Nov 2013

Keywords

  • Approximation algorithm
  • Operation-based performance measure
  • Refurbishing flowshop
  • Weighted total completion time

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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