fa An Efficient Genetic Agorithm for Solving the Multi-Mode Resource-Constrained Project Scheduling Problem Based on Random Key Representation Research Paper مقاله پژوهشی In this paper, a new genetic algorithm (GA) is presented for solving the multi-mode resource-constrained project scheduling problem (MRCPSP) with minimization of project makespan as the objective subject to resource and precedence constraints. A random key and the related mode list (ML) representation scheme are used as encoding schemes and the multi-mode serial schedule generation scheme (MSSGS) is considered as the decoding procedure. In this paper, a simple, efficient fitness function is proposed which has better performance compared to the other fitness functions in the literature. Defining a new mutation operator for ML is the other contribution of the current study. Comparing the results of the proposed GA with other approaches using the well-known benchmark sets in PSPLIB validates the effectiveness of the proposed algorithm to solve the MRCPSP. In this paper, a new genetic algorithm (GA) is presented for solving the multi-mode resource-constrained project scheduling problem (MRCPSP) with minimization of project makespan as the objective subject to resource and precedence constraints. A random key and the related mode list (ML) representation scheme are used as encoding schemes and the multi-mode serial schedule generation scheme (MSSGS) is considered as the decoding procedure. In this paper, a simple, efficient fitness function is proposed which has better performance compared to the other fitness functions in the literature. Defining a new mutation operator for ML is the other contribution of the current study. Comparing the results of the proposed GA with other approaches using the well-known benchmark sets in PSPLIB validates the effectiveness of the proposed algorithm to solve the MRCPSP. Combinatorial Optimization , Multi-mode project scheduling , Resource constraints , Genetic Algorithm , Random key representation , Combinatorial Optimization , Multi-mode project scheduling , Resource constraints , Genetic Algorithm , Random key representation , 905 924 http://system.khu.ac.ir/ijsom/browse.php?a_code=A-10-496-1&slc_lang=fa&sid=1 Mohammad Hassan Sebt Mohammad Hassan Sebt sebt@aut.ac.ir 1003194753284600189 1003194753284600189 Yes Amirkabir University of Technology, Tehran, Iran Amirkabir University of Technology, Tehran, Iran Mohammad Reza Afshar Mohammad Reza Afshar m.afshar67@aut.ac.ir 1003194753284600190 1003194753284600190 No Amirkabir University of Technology, Tehran, Iran Amirkabir University of Technology, Tehran, Iran Yagub Alipouri Yagub Alipouri yalipouri@aut.ac.ir 1003194753284600191 1003194753284600191 No Amirkabir University of Technology, Tehran, Iran Amirkabir University of Technology, Tehran, Iran