فهرست مطالب پرهام صوفی

One of the most important issues in the field of production scheduling, which has recently received much attention from researchers, is Dual Resource Constrained Flexible Job Shop Scheduling Problem (DRCFJSP). To deal with unexpected disruptions such as machine breakdowns, the job schedule must be robust so that in the event of a malfunction, the job schedule works properly and deviate less from the optimal solution. The purpose of this paper is to study the DRCFJSP problem with possible scenarios of machine failure or workshop disruption.

In solving the under-studied problem, the assignment of jobs and the sequence of operations on each machine should be done in such a way that under any possible scenario, the maximum completion time is minimized so that the weight combination of system performance in average mode, system performance in worst mode, the penalty for violating the time window constraints of the due dates and the variance of the objective function value is optimal according to different scenarios. For this purpose, a Robust Scenario-based Stochastic Programming (RSSP) model based on a mixed integer linear programming model has been presented for this problem and has been solved by Gams software for validation in small and medium-sized problems. Also, due to the Np-hard nature of this problem, a meta-heuristic method based on Genetic Algorithm (GA) is proposed for solving the large-sized problems. Also, the results of a case study in Alborz Yadak company related to the problem of the research are reported in the article.

The results of the proposed RSSP model indicate that GAMS software is able to solve these problems up to medium sizes in an acceptable time and achieve a controlled and robust solution. Numerical results also show the proper performance of the proposed GA as an alternative to solve the RSSP model in the large-sized problems.

Originality/Value: 

In this paper, DRCFJSP problem is studied with possible scenarios of machine failure or disruption in the workshop. Also, a RSSP model according to the mixed integer linear programming formulation and a meta-heuristic Algorithm have been presented for mentioned problem in this article.

Nowadays, supplying sources from outside a company has become an important business approach. A lot of models have been developed to solve the supplier selection problem. Among them, multiple criteria decision making (MCDM) has been used by lots of authors and researchers with acceptable results. A review of literature on supplier selection shows that although supplier selection is a multi-objective problem, the nature of this multi objective problem has remained unknown. In many cases, except cost, other important parameters like quality, lead time and risk are not considered. Also practically, the effect of the nature of uncertain and imprecise facts on decision making like objectives, constraints and parameters cant be disregarded. To take account of these uncertainties, this research uses fuzzy method. Discount and costs due to inventory keeping in the goal function have been considered simultaneously. We also have considered objectives like decreasing the defected parts, and late delivery.