A genetic algorithm with a new local search method for solving the multimode resource-constrained project scheduling problem

The existence of limited resources and precedence relations between activities makes project scheduling a difficult task. In this paper, the multimode resource-constrained project scheduling problem (MRCPSP) as one of the important project scheduling problems is focused. In this regard, a genetic algorithm (GA) is proposed for solving the multimode resource-constrained project scheduling problem (MRCPSP) improved by a new local search method. The Activity Mode List (AML) is used as encoding and the multimode serial schedule generation scheme (MSSGS) is employed as the decoding procedure. The aim of the suggested local search is maximum use of existed nonrenewable resources of the project such that its makespan is decreased. For this purpose, the local search procedure allocates the unused nonrenewable resources of each feasible solution to the activities with lower total float. Comparing results of the proposed method with other ones using the set J20 in Project Scheduling Problem Library (PSPLIB) validates the effectiveness of the proposed algorithm to solve the MRCPSP.