A bicriterion approach to common flow allowances due window assignment and scheduling with controllable processing times

Dujuan Wang, Yunqiang Yin, Edwin Tai Chiu Cheng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

18 Citations (Scopus)

Abstract

We investigate a single-machine scheduling problem for which both the job processing times and due windows are decision variables to be determined by the decision maker. The job processing times are controllable as a linear or convex function of the amount of a common continuously divisible resource allocated to the jobs, where the resource allocated to the jobs can be used in discrete or continuous quantities. We use the common flow allowances due window assignment method to assign due windows to the jobs. We consider two performance criteria: (i) the total weighted number of early and tardy jobs plus the weighted due window assignment cost, and (ii) the resource consumption cost. For each resource consumption function, the objective is to minimize the first criterion, while keeping the value of the second criterion no greater than a given limit. We analyze the computational complexity, devise pseudo-polynomial dynamic programming solution algorithms, and provide fully polynomial-time approximation schemes and an enhanced volume algorithm to find high-quality solutions quickly for the considered problems. We conduct extensive numerical studies to assess the performance of the algorithms. The computational results show that the proposed algorithms are very efficient in finding optimal or near-optimal solutions. Naval Research Logistics, 64: 41–63, 2017.
Original languageEnglish
Pages (from-to)41-63
Number of pages23
JournalNaval Research Logistics
Volume64
Issue number1
DOIs
Publication statusPublished - 1 Feb 2017

Keywords

  • controllable processing times
  • due window assignment
  • FPTAS
  • resource allocation
  • scheduling

ASJC Scopus subject areas

  • Modelling and Simulation
  • Ocean Engineering
  • Management Science and Operations Research

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