A PARALLEL SIMULATED ANNEALING (PSA) FOR SOLVING PROJECT SCHEDULING PROBLEM WITH DISCOUNTED CASH FLOW POLICY IN PRICING STRATEGY OF THE PROJECT SUPPLIERS

Resource-constrained project scheduling problem is known as a NP-Hard problem in literature. In this research, discounted cash flow policy is suggested for the resources-constrained project scheduling problem for the first time while in classic models, it has been assumed that price of the required resources is fixed for performing the activities and resources can be prepared only with one price rate in the market. Goal of this problem is to determine optimal starting time of the project activities considering precedence constraints and the available resources such that the project completion time can be minimized. In order to solve the proposed model, a hybrid algorithm based on two algorithms i.e. genetic and simulated annealing has been suggested. In this method, genetic algorithm has been designed as the main framework of the proposed method and simulated annealing method as a new operator and in order to improve local search of the main algorithm. Since values of the parameters have considerable effect on efficiency of these algorithms, therefore, a new statistical approach based on the stepwise regression has been presented to set the proposed algorithms parameters. Results of the calculations show high efficiency of proposed algorithm in terms of solution time and optimal solutions.