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

A multi-objective grey project selection scheduling model is proposed.The model takes into account the resource and budget limitations.A modified SFLA algorithm is proposed to tackle the problem.Monte Carlo simulation is used to handle the grey uncertainty.The proposed SFLA showed great diversity and acceptable intensification. 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.