چكيده به لاتين
In this study, a Multi-skilled Resource-Constrained Flexible Flow Shop Scheduling Problem (MSRC-FFSSP) has been developed. In other words, to process any job at each machine, in addition to the machine, a set of required human resources with different skills must be available. According to their skills, each of the human resources can perform at least one job or at most N jobs, and each job can be performed by at least one set of different skills of human recources. For this problem, three new Mixed Integer Linear Programming (MILP) models, the first one considering one set of human resources to process jobs, the second one considering multi sets of human resources to process each job, and the third one with one set of human resources to process jobs under uncertainty, are formulated. For the first two problems, whose parameters are considered deterministic, bi objective functions to simultaneously minimize the total completion time of jobs and the total idle time of human resources, and for the third problem under uncertainty, only an objective function of minimizing the total completion time of jobs are considered. Moreover, to prove the applicability of this problem, a case study has been conducted in the realm of preventive maintenance within deterministic scenarios and corrective maintenance under uncertain conditions. To solve the model on a small-scale, an operation research software is used, and to solve it on a large-scale, due to the fact that this problem is NP-hard, two meta-heuristic algorithms of Genetic and Simulated Annealing, whose parameters are tune by the Taguchi method, are presented. Finally, numerical results have been presented to validate the model, along with the analysis of the idle time of human resources.