A hyper-heuristic based ensemble genetic programming approach for stochastic resource constrained project scheduling problem

HaoJie Chen, Guofu Ding, Shengfeng Qin, Jian Zhang

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

In project scheduling studies, to the best of our knowledge, the hyper-heuristic collaborative scheduling is first-time applied to project scheduling with random activity durations. A hyper-heuristic based ensemble genetic programming (HH-EGP) method is proposed for solving stochastic resource constrained project scheduling problem (SRCPSP) by evolving an ensemble of priority rules (PRs). The proposed approach features with (1) integrating the critical path method into the resource-based policy class to generate schedules; (2) improving the existing single hyper-heuristic project scheduling research to construct a suitable solution space for solving SRCPSP; and (3) bettering genetic evolution of each subpopulation from a decision ensemble with three different local searches in corporation with discriminant mutation and discriminant population renewal. In addition, a sequence voting mechanism is designed to deal with collaborative decision-making in the scheduling process for SRCPSP. The benchmark PSPLIB is performed to verify the advantage of the HH-EGP over heuristics, meta-heuristics and the single hyper-heuristic approaches.
Original languageEnglish
Article number114174
Number of pages15
JournalExpert Systems with Applications
Volume167
Early online date31 Oct 2020
DOIs
Publication statusPublished - 1 Apr 2021

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