A matheuristic for the resource-constrained project scheduling problem
Coelho, José
Coelho, José
Publication Type
Journal article with impact factor
Editor
Supervisor
Publication Year
2024
Journal
European Journal of Operational Research
Book
Publication Volume
319
Publication Issue
3
Publication Begin page
711
Publication End page
725
Publication Number of pages
Collections
Abstract
This paper presents a matheuristic solution algorithm to solve the well-known resource-constrained project scheduling problem (RCPSP). The problem makes use of a restricted neighbourhood method using an activity selection and a search space restriction module and implements them as two alternative search algorithms. The first algorithm makes use of the best-performing components of the branch-and-bound procedures from the literature, and embeds them into a greedy neighbourhood search. The second matheuristic implements the exact branch-and-bound procedures into a known and well-performing meta-heuristic search algorithm. Computational experiments have been carried out on seven different datasets consisting of 10,000+ project instances. Experiments reveal that the choice of exact algorithm is key in finding high-quality solutions, and illustrate that the trade-off between selecting an activity set size and search space restriction depends on the specific implementation. The computational tests demonstrate that the matheuristic discovered 24 new best known solutions that could not be found by either a meta-heuristic or an exact method individually. Moreover, a new benchmark dataset has been proposed that can be used to develop new matheuristic search procedures to solve the problem consisting of 461 instances from the literature.
Research Projects
Organizational Units
Journal Issue
Keywords
Project scheduling, Matheuristic, Branch-and-bound, Project Network Indicator, Neighbourhood Search