An Agile Adaptive Biased-Randomized Discrete-Event Heuristic for the Resource-Constrained Project Scheduling Problem
Martin, Xabier A. (Universitat Politècnica de València)
Herrero, Rosa (Universitat Pompeu Fabra)
Juan, Ángel A (Universitat Politècnica de València)
Panadero, Javier (Universitat Autònoma de Barcelona. Departament d'Arquitectura de Computadors i Sistemes Operatius)

Data:	2024
Descripció:	21 pàg.
Resum:	In industries such as aircraft or train manufacturing, large-scale manufacturing companies often manage several complex projects. Each of these projects includes multiple tasks that share a set of limited resources. Typically, these tasks are also subject to time dependencies among them. One frequent goal in these scenarios is to minimize the makespan, or total time required to complete all the tasks within the entire project. Decisions revolve around scheduling these tasks, determining the sequence in which they are processed, and allocating shared resources to optimize efficiency while respecting the time dependencies among tasks. This problem is known in the scientific literature as the Resource-Constrained Project Scheduling Problem (RCPSP). Being an NP-hard problem with time dependencies and resource constraints, several optimization algorithms have already been proposed to tackle the RCPSP. In this paper, a novel discrete-event heuristic is introduced and later extended into an agile biased-randomized algorithm complemented with an adaptive capability to tune the parameters of the algorithm. The results underscore the effectiveness of the algorithm in finding competitive solutions for this problem within short computing times.
Ajuts:	European Commission 101092612 European Commission 101057294 Agencia Estatal de Investigación PID2022-138860NB-I00 Ministerio de Ciencia e Innovación RED2022-134703-T
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Adaptive algorithms ; Agile optimization ; Biased-randomization ; Discrete-event heuristics ; Resource-constrained project scheduling
Publicat a:	Mathematics, Vol. 12, Issue 12 (June 2024) , art. 1873, ISSN 2227-7390

DOI: 10.3390/math12121873

21 p, 1.9 MB

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