A new fuzzy multi-objective multi-mode resource-constrained project scheduling model

In this paper, a new model is developed to address the so-called multi-objective multi-mode resource-constrained project scheduling problem under uncertainty conditions in the problem parameters. The two objective functions are minimising the project NPV and the project makespan, which is the first contribution of the current research. The proposed model is much more realistic one in comparison to previously developed model. This approach explicitly considers the risk acceptance level and the optimism of the project managers in the final decision, which are the main contributions of the current research. To show the efficiency of the proposed model in real applications, an efficient metaheuristic method based on memetic algorithm and cuckoo optimisation algorithm is developed to solve this problem, which is in fact, the second contribution of the paper. The algorithm embeds the cuckoo optimisation algorithm as a powerful local search method inside the genetic algorithm to improve its performance. To test the algorithm performance, a number of test problems from PSPLIB library were taken and then the proposed algorithm and the famous NSGA-II were examined over these problems, separately. The results were compared according to three different criteria. Computational results show that the proposed memetic-cuckoo algorithm is more efficient than the NSGA-II according to three different comparison criteria.