New meta-heuristics for the resource-constrained project scheduling problem

In this paper, we study the resource-constrained project scheduling problem and introduce an annealing-like search heuristic which simulates the cooling process of a gas into a highly-ordered crystal. To achieve this, we develop diversification procedures that simulate the motion of high energy molecules as well as a local refinement procedure that simulates the motion of low energy molecules. We further improve the heuristic by incorporating a genetic algorithm framework. The meta-heuristic algorithms are applied to Kolisch’s PSPLIB J30, J60 and J120 RCPSP instances. Experimental results show that they are effective and are among the best performing algorithms for the RCPSP.