Solving a grey project selection scheduling using a simulated shuffled frog leaping algorithm

摘要

This paper considers the integrated problem of project selection and scheduling in a tri-objective grey environment. First a pure integer model is proposed to optimize the time-dependent profits, total costs and total unused resources. Then the model is converted to a grey equivalent by considering some parameters as grey numbers. A discussion is given on the relations between these parameters and constraints of the model. Since the problem is strongly NP-hard, a modified grey shuffled frog leaping algorithm (GSFLA) is proposed to tackle the problem. To handle the greyness of the model, GSFLA is embedded in a loop of Monte Carlo simulation. The proposed algorithm is compared with two well-known meta-heuristics, non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization (MO-PSO). The results indicate that the proposed method shows better performance, both in intensification and diversification.