S. Rodríguez Ballesteros, J. Alcaraz Soria, L. Antón Sánchez
The bi-objective resource-constrained project scheduling problem with time-dependent resource costs is to schedule a set of activities subject to precedence and resource constraints such that the makespan and the total cost for resource usage is minimized. In such a multi-objective context, solving the aforementioned problem poses a challenge, as both objectives conflict with each other, giving rise to a set of trade-off optimal solutions, commonly known as the Pareto front. Given that many medium or large-sized instances of this problem cannot be solved by exact methods, the development of metaheuristics for approximating the Pareto front is necessary, and six multi-objective evolutionary algorithms have been implemented. To assess their performance, a computational study is conducted, choosing a benchmark of bi-criteria resource-constrained project scheduling problems and applying a set of performance measures to the solution sets obtained by each methodology.
Keywords: Metaheuristics, resource-constrained project scheduling problem, multi-objective optimization, Pareto front, performance indicators
Scheduled
GT10.HEUR4 Invited Session
November 8, 2023 4:00 PM
CC3: Room 1