Faezeh Motevalli-Taher; Mohammad Mahdi Paydar
Abstract
In this study, tactical decisions considering the material and financial flows in a supply chain have been made. To achieve these aims and some effective solutions, a multi-objective mathematical model proposed for an integrated supply chain master planning problem. The multi-product, multi-period and ...
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In this study, tactical decisions considering the material and financial flows in a supply chain have been made. To achieve these aims and some effective solutions, a multi-objective mathematical model proposed for an integrated supply chain master planning problem. The multi-product, multi-period and capacitated supply chain network has three objective functions. Two first objective functions are maximizing the net present value of manufacturing centers and suppliers’ cash flow, and the third one minimizes the market price of the final product. Besides we considered the market price as a key variable in the model and investigate its effects. Then, improved multi-choice goal programming is used to transform the multi-objective model to its single-objective one. To find out the appropriateness of the proposed model, the results of an industrial example are illustrated, and sensitivity analyses to evaluate the results are provided to obtain better insight and access to different aspects of the problem.
Iraj Mahdavi; Sara Firouzian; Mohammad Mahdi Paydar; Mahdi Saadat
Abstract
Cell formation problem (CFP) is one of the main problems in cellular manufacturing systems. Minimizing exceptional elements and voids is one of the common objectives in the CFP. The purpose of the present study is to propose a new model for cellular manufacturing systems to group parts and machines in ...
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Cell formation problem (CFP) is one of the main problems in cellular manufacturing systems. Minimizing exceptional elements and voids is one of the common objectives in the CFP. The purpose of the present study is to propose a new model for cellular manufacturing systems to group parts and machines in dedicated cells using a part-machine incidence matrix to minimize the voids. After identifying the exceptional elements, the machines required for processing the remained operations of corresponding parts which are not processed in the dedicated cells are specified. This results in a new matrix called part family-machine. Then, by clustering the part family-machine incidence matrix, the part families that should be assigned to a specific cell to achieve the highest similarity can be determined. The similarity can be translated to sharing machines required for completing the processes and form new cells called shared cells to minimize the number of exceptional elements and voids. Unlike previous models in which the similarity is considered only in the dedicated cells, in the proposed model, the similarity would be monitored and observed in the entire production process. Due to the complexity of our model, two meta-heuristic algorithms including artificial immune system (AIS) and simulated annealing (SA) are proposed. The efficiency of the algorithms is compared to that of exact solutions. Also, the algorithms are compared regarding the quality of solutions. Finally, according to grouping efficacy measure, SA algorithm has a superior performance in comparison with AIS by spending less CPU time.