Designing a new multi-objective mathematical model for scheduling multifunctional machines taking into account the quality of manufactured parts
Volume 9, Issue 2, Summer 2019, Pages 124-137
Mohammad Esfandiar, Mostafa Kazemi, Bahman Naderi, Alireza Pouya
Abstract The purpose of this paper is to design a multi-objective mathematical programming model for scheduling multifunctional machines in a production cell. For this purpose, a multiobjective invasive weed algorithm was proposed and its solution results were compared with multi-objective and genetic particle swarm algorithms. Algorithm parameters were adjusted according to Taguchi method. The innovation of this article, on the one hand, is in implementing the idea of machine processing speed in the production of parts with different qualities. In other words, to ensure quality, processing speed and loading rate are adjusted in the machine, and on the other hand, a multi-objective algorithm with a new chromosome structure was designed to optimize the model. To analyze the performance of solution algorithms, thirty sample problems with different dimensions were designed and performed ten times each. The analysis of the results showed that the multi-objective invasive weed-based algorithm was able to solve and answer problems more than other algorithms.
New combination of robust planning with credit constraints for responsive-dependent closed-loop supply chain network under uncertainty and disruptions
Volume 6, Issue 4, Winter 2017, Pages 213-227
Alireza Arshadikhamseh, Alireza Hamidieh, bahman Naderi
Abstract Today, supply chain networks in a competitive business environment are faced with the occurrence of potential disruptions, uncertain nature of business parameters and constant changes in market demand that affect the efficiency and performance of the network. This research has developed a new stable-feasibility possibility combination for designing a multi-product closed-loop supply chain network under uncertainty conditions to develop a new approach to planning. Mathematics of credit limitation has been used. The above network has been designed with the objectives of maximizing accountability, reliability and cost minimization. . Reliable models based on credit constraint planning and new robust-credit constraint combination were presented and evaluated using real data from a national industrial project. The results show the proposed robust new combination with average cost-effectiveness and minimum standard deviation , Has improved the stability of the model and its effectiveness.