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

Chen, HaoJie, Ding, Guofu, Qin, Sheng-feng and Zhang, Jian (2020) A hyper-heuristic based ensemble genetic programming approach for stochastic resource constrained project scheduling problem. Expert Systems with Applications. p. 114174. ISSN 0957-4174 (In Press)

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Official URL: https://doi.org/10.1016/j.eswa.2020.114174

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.

Item Type: Article
Uncontrolled Keywords: Ensemble decision, Genetic programming, Hyper-heuristics, Priority rule, Stochastic resource constrained project scheduling
Subjects: G400 Computer Science
Department: Faculties > Arts, Design and Social Sciences > Design
Depositing User: John Coen
Date Deposited: 06 Nov 2020 13:53
Last Modified: 06 Nov 2020 14:00
URI: http://nrl.northumbria.ac.uk/id/eprint/44705

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