A generalized heuristic learning approach to project scheduling problems with resource constraints

Li Yen Shue, Sheng Tun Li

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

We present a generalized heuristic learning algorithm and a solution approach for its implementation in solving project scheduling problems with resource constraints. The search process of the algorithm is characterised by the complete heuristic learning process: state selection, heuristic learning, and search path review. The heuristic learning process enables the algorithm to continue to improve the state selection decision. The heuristic learning threshold of the algorithm allows users to specify solution quality, optimal or near-optimal solutions, with efficient computation. The implementation approach is based on the dynamic nature of activity status and resource availability of a project. It consists of states, state transition operator, heuristic estimate, and the cost of transition between states. The performance analysis of this algorithm with Patterson's 110 problem is presented.

Original languageEnglish
Pages (from-to)204-214
Number of pages11
JournalJournal of the Chinese Institute of Industrial Engineers
Volume25
Issue number3
DOIs
Publication statusPublished - 2008 Jan 1

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering

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