An Agile Adaptive Biased-Randomized Discrete-Event Heuristic for the Resource-Constrained Project Scheduling Problem

Xabier A. Martin, Rosa Herrero, Angel A. Juan () and Javier Panadero
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Xabier A. Martin: Research Center on Production Management and Engineering, Universitat Politècnica de València, Plaza Ferrandiz-Carbonell, 03801 Alcoy, Spain
Rosa Herrero: TecnoCampus, Universitat Pompeu Fabra, Av. Ernest Lluch, 32, 08302 Mataró, Spain
Angel A. Juan: Research Center on Production Management and Engineering, Universitat Politècnica de València, Plaza Ferrandiz-Carbonell, 03801 Alcoy, Spain
Javier Panadero: Department of Computer Architecture and Operating Systems, Universitat Autònoma de Barcelona, Carrer de les Sitges, 08193 Bellaterra, Spain

Mathematics, 2024, vol. 12, issue 12, 1-21

Abstract: 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.

Keywords: resource-constrained project scheduling; discrete-event heuristics; biased-randomization; adaptive algorithms; agile optimization (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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