Using metaheuristics in multiobjective resource constrained project scheduling

Although single objective metaheuristics are widely spread and applied in many combinatorial optimisation problems, only very recently have multiobjective metaheuristics (MOMH) been designed and used in practice. They aim at obtaining good approximations of the set of nondominated solutions of a problem, in an efficient way. In this work, we have applied multiobjective versions of simulated annealing and taboo search to the resource constrained project scheduling problem (RCPSP), in order to minimise the makespan, the ‘weighted’ lateness of activities and the violation of resource constraints. Computational experience performed on randomly generated instances shows that this general approach is flexible, effective and able to deal with multiple objectives and with variations in the problem structure.