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- 저자 : Rustem Adamovich Shichiyakh (검색결과 2 건)
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Rustem Adamovich Shichiyakh,Olga Yu Voronkova,Inara K. Shakhbanova,Chulpan Ya Shafranskaya,Svetlana V. Titova,Andrey L. Poltarykhin 대한산업공학회 2021 Industrial Engineeering & Management Systems Vol.20 No.4
With regard to environmental concerns, energy consumption is another major issue in high-performance systems. This paper examines the scheduling problem in a multi-machine system where the machine's engine speed can be adjusted over an interrupt interval. Adjusting the CPU by sacrificing the completion time delivers flexibility to minimize the cost of electricity in terms of energy savings. Traditional research focuses on machine planning on assignment of work and sequencing to optimize specific target functions that are defined to complete work time. In the above circumstances, the purpose of the study is to assign the works to machines, as well as to determine the sequence of tasks and the speed of each machine to minimize the objective function, including to minimize tardiness penalty and energy cost with sequence dependent set-up times. We proposed two fragmentary algorithms based on the PSO and Genetic Algorithm (GA) algorithms. In this paper, the application of these two algorithms for minimizing tardiness penalty and energy cost with sequence dependent set-up times is examined. Finally, the algorithms are compared and the results are compared.
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An Integrated Multi-Objective Approach to Managing Supply Risks in a Flexible Supply Chain
Aceng Muhtaram Mirfani,Dedy Achmad Kurniady,Alim Al Ayub Ahmed,Rustem Adamovich Shichiyakh,Mustafa M. Kadhim,Ali Yaseen Hasan,Mahdi Ghaffari 대한산업공학회 2021 Industrial Engineeering & Management Systems Vol.20 No.4
Nowadays, it is necessary to paying attention to the opportunities and threats in the field of industry and trade, and evaluate the ability of industries and companies in dealing with uncertainties and existing risks, and it is very im-portant to manage supply chain risk. The main purpose of this study is to be careful against risky suppliers and reduc-ing the injury rate in the event of a disruption. Therefore, in this regard, a multi-stage mixed integer programming model with a proactive approach has been used; that in the first stage, the model reports the amount of supply from suppliers without considering the risk criterion, and at the same time, it seeks to optimal state of minimization the supply chain costs (including purchase cost, shipping, maintenance, supplier selection and return goods). In the second stage, after the suppliers which supplying the parts, have been identified, the model seeks to minimize the identified risks of suppliers under different scenarios. In the third stage, the model tries to achieve an optimal state of supplying the parts from less risky suppliers. In the continuation of this study, an integrated multi-objective programming model has been designed, which will be solved by the epsilon constraint method, and the best output will be reported from the Pareto’s optimal set of answers; Finally the results of the model will be compared in two multi-stage and integrated multi-objective modes and the correctness of the performance is confirmed.
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