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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.
Design of a Two-tier Supply Chain Based on Integration, Pricing, Routing, and Inventory Control
Aruzhan Jussibaliyeva,Ius Rusnati,Aan Komariah,Aigul Kurmanalina,Nikolay N. Reutov,Gulnar Temirgaliyevna Kunurkulzhaeva,Alim Al Ayub Ahmed,Ravil Akhmadeev,Supat Chupradit 대한산업공학회 2021 Industrial Engineeering & Management Systems Vol.20 No.4
This paper integrates decisions about the three key components of the supply chain including pricing, routing and inventory control, and multi-product multi-cycle in a two-tier supply chain; includes a manufacturer and a collection of dedicated retailers. In addition to pricing, inventory management and distribution planning, production planning is also considered in the study. The goal is to maximize profits in the supply chain, where products are delivered to retailers by a fleet of limited-capacity identical vehicles under a multiple-delivery strategy. Also, limited production and storage capacity and unauthorized shortages are assumed. The proposed model will then be solved using CPLEX software package in GAMS environment and genetic algorithm in Matlab software to determine the optimal supply chain policy.
A Comprehensive Optimization Approach Based on Cloud Computing for Logistic Sharing System Planning
I Gusti Ayu Purnamawati,Atheer Y. Oudah,Hasbullah Bin Othman,Irwan Bin Ibrahim,A. Heri Iswanto,Aan Komariah,Afanasiy Afanasievich Sergin,Imanuddin Hasbi,Yasser Fakri Mustafa 대한산업공학회 2022 Industrial Engineeering & Management Systems Vol.21 No.3
Due to the global size of the production space and a large number of suppliers and service recipients, sequencing op-erations and logistics are very important in achieving optimal production system performance, reducing costs and reducing time. Since, in the cloud manufacturing space, each of the production activities of a product can be assigned to different resources in different places, logistics services are needed to communicate between these resources. Thus, the study aims to propose a model for a comprehensive optimization approach based on cloud computing for logistic sharing system planning. Given the results, regarding both operational services and logistics services in the cloud manufacturing system, in addition to the optimal allocation of activities and logistics services, it is possible to plan and schedule the sequence of operations and logistics to minimize the total cost of the cloud production system. Stud-ies are also being conducted on sharing logistics systems in the cloud.
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.