Abstract
This paper presents a genetic algorithm (SA) for the classical multimode resource-constrained project scheduling problem (MRCPSP). The objective is makespan minimization of the project. A new precedence feasible multi point forward backward crossover operator is presented. SA and GA are used in tandem to ensure balance in exploration and exploitation of search space. SA is employed as local search procedure, due to its stochastic neighborhood selection strategy to escape local optima hence a good exploitation strategy; and GA as exploration strategy due to its large number of population. Computational investigations are carried out on standard data set problems from PSPLIB and it is proved that hybridization of GA with SA gives competitive performance when compared with currently available algorithms
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
