Genetic local search for resource-constrained project scheduling under uncertainty

Shixin Liu, Kai Leung Yung, W. H. Ip

Research output: Journal article publicationJournal articleAcademic researchpeer-review

7 Citations (Scopus)

Abstract

Global manufacturing can be viewed as a project-oriented environment, where an effective project baseline schedule can serve as a basis for planning external activities, such as material procurement, preventive maintenance and commitment to shipping dates to customers. However, real life project scheduling often encounters imprecise activity durations and resource-constraints. The fuzzy set theory provides natural modeling tools for dealing with imprecise activity durations. In this paper, based on the fuzzy set theory, a specific genetic local search (GLS) algorithm is designed to solve fuzzy resource-constrained project scheduling problems. A precedence feasible activity list is applied as a solution representation, and specially designed recombination operators and local search processes are used in our algorithm. The roulette wheel selection and the elite retaining model are incorporated to generate a new population for the next generation. A practical project schedule with different resource availability levels is used in computational experiments. Computational results show that the GLS algorithm is effective for solving this kind of problem.
Original languageEnglish
Pages (from-to)347-363
Number of pages17
JournalInternational Journal of Information and Management Sciences
Volume18
Issue number4
Publication statusPublished - 1 Dec 2007

Keywords

  • Fuzzy constraint satisfaction
  • Fuzzy numbers
  • Genetic local search
  • Project scheduling

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Management Information Systems
  • Strategy and Management
  • Industrial and Manufacturing Engineering
  • Information Systems and Management

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