Efficient metaheuristic algorithms to solve the resource-constrained project scheduling problem with different sizes

The resource-constrained project scheduling problem (RCPSP) is a problem concerned withoperational research and project management, which has been highly regarded by researchers inrecent years due to its strategic and practical nature. In the present study, this problem is modeledconsidering the major objectives including the minimization of the project makespan and theminimization of the maximum project execution cost in one day. It should be noted that allpossible prerequisite relationships between the activities of a project were taken into account andthe proposed model was executed for three real projects of different sizes using metaheuristicalgorithms, including genetic algorithm (GA), particle swarm optimization algorithm (PSO), anddifferential evolution algorithm (DE). As indicated by the obtained results, the DE and PSOalgorithms proved to be highly efficient, respectively, for large-scale and medium-scale projectscompared to GA. On the whole, it is not recommended to use metaheuristic algorithms forsolving small-scale projects.

کلیدواژه ها:

Project scheduling ، Resource constraint ، Genetic algorithm (GA) ، Particle swarm optimization (PSO) algorithm ، Differential evolution (DE) algorithm