Combining Monte-Carlo and hyper-heuristic methods for the multi-mode resource-constrained multi-project scheduling problem

Asta, Shahriar and Karapetyan, Daniel and Kheiri, Ahmed and Özcan, Ender and Parkes, Andrew J. (2016) Combining Monte-Carlo and hyper-heuristic methods for the multi-mode resource-constrained multi-project scheduling problem. Information Sciences, 373. pp. 476-498. ISSN 0020-0255

[thumbnail of MISTA2013]
MISTA2013.pdf - Accepted Version
Available under License Creative Commons Attribution-NonCommercial-NoDerivs.

Download (448kB)


Multi-mode resource and precedence-constrained project scheduling is a well-known challenging real-world optimisation problem. An important variant of the problem requires scheduling of activities for multiple projects considering availability of local and global resources while respecting a range of constraints. A critical aspect of the benchmarks addressed in this paper is that the primary objective is to minimise the sum of the project completion times, with the usual makespan minimisation as a secondary objective. We observe that this leads to an expected different overall structure of good solutions and discuss the effects this has on the algorithm design. This paper presents a carefully-designed hybrid of Monte-Carlo tree search, novel neighbourhood moves, memetic algorithms, and hyper-heuristic methods. The implementation is also engineered to increase the speed with which iterations are performed, and to exploit the computing power of multicore machines. Empirical evaluation shows that the resulting information-sharing multi-component algorithm significantly outperforms other solvers on a set of “hidden” instances, i.e. instances not available at the algorithm design phase.

Item Type:
Journal Article
Journal or Publication Title:
Information Sciences
Additional Information:
This is the author’s version of a work that was accepted for publication in Information Sciences. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Information Sciences, 373, 2016 DOI: 10.1016/j.ins.2016.09.010
Uncontrolled Keywords:
?? hybrid heuristicshyper-heuristicsmetaheuristicsmonte carlo tree searchmulti-project schedulingpermutation based local searchcontrol and systems engineeringtheoretical computer sciencesoftwarecomputer science applicationsinformation systems and managementa ??
ID Code:
Deposited By:
Deposited On:
21 Nov 2017 20:08
Last Modified:
15 Jul 2024 17:20