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Dedy Achmad Kurniady,Asep Denih,Tri Rijanto,Elena Igorevna Artemova,Huynh Tan Hoi,Liu Zhaojun,Lilis Holisoh Nuryani,Aan Komariah 대한산업공학회 2022 Industrial Engineeering & Management Systems Vol.21 No.2
In this paper, the scheduling of the flexible flow shop scheduling problem without unemployment is considered by considering the sequence-dependent preparation times with parallel and identical machines in each workstation in order to minimize the maximum completion time that has been done so far. The assumption of the existence of sequence-dependent preparation times has not been observed in the literature on the issue of flexible workflow without unemployment. In this study, a mixed integer programming model for the problem is first developed. Since the problem under study is one of the NP-hard problems and the mathematical model solving software is not able to obtain the optimal solution of relatively large problems at a reasonable time, to provide a meta-heuristic method of genetic algorithm to obtain optimal solutions or close to optimal for the problem. The computational results show the relatively good performance of the genetic algorithm for solving problems in less time than the mathematical programming model.
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.
Multi-objective Mathematical Modeling for Scheduling Machines in Parallel with Batch Processors
Evy Segarawati Ampry,Aan Komariah,Dedy Achmad Kurniady,Muhammad Rafiq,Asep Priatna,Muneam Hussein Ali,Haydar Abdulameer Marhoon,Lakshmi Thangavelu,Purnima Chaudhary 대한산업공학회 2022 Industrial Engineeering & Management Systems Vol.21 No.2
In this paper, the problem of scheduling the production of unrelated parallel machines to simultaneously minimize the goals of production time span, early and late fines, and the cost of purchasing machines is investigated, and a two-objective mathematical model is considered considering clearance and preparation times and limit capacity. Due to faster and cheaper operations with batch processors and increasing the efficiency of operating systems, all machines are batch processors. Initially, the model is coded and executed using the exact method in GAMS software. Due to the hard-NP nature and complex nature of the problem, a multi-objective meta-heuristic algorithm based on the coordination search method is proposed and designed. Then Taguchi method is used to find the best level for the algorithm parameters, and two examples of problems in different dimensions of tasks and machines are presented and solved by this proposed algorithm. The results of the calculations show the efficiency of this algorithm to generate more solutions at a much lower solution time.
Ahmad Kultur Hia,Akhmetova Gulmira,Nurpeiis Gulshat Sakenkyzy,Kenzhegaliyeva Zita,Muneam Hussein Ali,Ghaffar Ahmad Hussein,A. Heri Iswanto,Dedy Achmad Kurniady,Dani Hidayatuloh 대한산업공학회 2022 Industrial Engineeering & Management Systems Vol.21 No.2
Reliability is referred to as quality over time and one of the dimensions of quality. Improving product reliability is one of the major concerns in manufacturing and service processes that can be achieved by applying statistical process control. Statistical control chart is a process monitoring tool that is widely used in the manufacturing industry and can be used to monitor the failure process. The development of control charts for this purpose is one of the topics of interest to researchers in the field of reliability. However, research in this area has been limited to the development of control charts for separate monitoring of statistical indicators. In the present study, a new control chart will be proposed to monitor failure times and product reliability. The purpose of this chart is to simultaneously monitor various parameters of failure time distribution. For this purpose, in this research, normal distribution and normal log are investigated
Optimizing the Issue of Blood Supply Chain Network Design with a Reliability Approach
Anik Yuesti,Paitoon Chetthamrongchai,Alim Al Ayub Ahmed,Vera Anitra,Surendar Aravindhan,Ravil Akhmadeev,Dedy Achmad Kurniady,Clara Neltje Meini Rotinsulu,M. Kavitha 대한산업공학회 2022 Industrial Engineeering & Management Systems Vol.21 No.2
Supply chain network design of a product is one of the primary and strategic measures in supply chain management that plays a vital role in supply chain performance. Since blood is a special commodity and has no substitute, supply chain management and optimization have a special place among researchers. In this research, for the first time, a two-objective nonlinear mixed integer model is presented to help make strategic and operational decisions in the blood supply chain. The first objective function is related to cost minimization and the second objective function is related to supply chain reliability maximization, which is considered as a series-parallel system. To check the validity of the model, a numerical example is solved using GAMS software, then using MOPSO meta-heuristic algorithm, the model is solved in larger dimensions and while comparing the performance criteria of multi-objective algorithms, the results are reviewed.