Modeling the diffusion of dexterity among workers in the multi-skilled resource-constrained project scheduling problem

This paper proposes a new mixed-integer mathematical formulation for the multi-objective multi-skilled resource-constrained project scheduling problem. The objectives of the proposed model are to minimize the make-span and cost of project, simultaneously. In this problem, the workforces can cooperate with each other in working groups to carry out required skills of activities. In the proposed model, workforces have different efficiencies in performing each of their skills and they can improve their efficiencies by learning from more efficient co-workers. Instructing relations between workers have been presented as multiple directed and weighted networks. The problem is NP-hard in the strong sense. Therefore, four multi-objective meta-heuristics have been developed to solve the problem. The performances of algorithms have been compared to each other in terms of convergence, diversity of solutions and computation time. The results show that each of the algorithms has been more successful in providing better results in terms of some performance measures.