Ayandegan Institute of Higher EducationInternational Journal of Research in Industrial Engineering2783-13378320190901An optimization model for aggregate production planning and control: a genetic algorithm approach2032249417810.22105/riej.2019.192936.1090ENS. M. AhmedDepartment of Industrial and Production Engineering, Jashore University of Science and Technology, Jahsore, Bangladesh.T. K. BiswasDepartment of Industrial and Production Engineering, Jashore University of Science and Technology, Jahsore, Bangladesh.C. K. NundyDepartment of Industrial and Production Engineering, Jashore University of Science and Technology, Jahsore, Bangladesh.Journal Article20190506In this paper, an optimization model for aggregate planning of multi-product and multi-period production system has been formulated. Due to the involvement of too many stakeholders as well as uncertainties, the aggregate production planning sometimes becomes extremely complex in dealing with all relevant cost criteria. Most of the existing approaches have focused on minimizing only production related costs, consequently ignored other cost factors, for instance, supply chain related costs. However, these types of other cost factors are greatly affected by aggregate production planning and its mismanagement often results in increased overall costs of the business enterprises. Therefore, the proposed model has attempted to incorporate all the relevant cost factors into the optimization model which are directly or indirectly affected by the aggregate production planning. In addition, the considered supply chain related costs have been segregated into two major categories. While the raw material purchasing, ordering, and inventory costs have been grouped into an upstream category, finished goods inventory, and delivery costs in the downstream category. The most notable differences with the other existing models of aggregate production planning are in the consideration of the cost factors and formulation process in the mathematical model. A real-life industrial case problem is formulated and solved by using a genetic algorithm to demonstrate the applicability and feasibility of the proposed model. The results indicate that the proposed model is capable of solving any type of aggregate production planning efficiently and effectively. https://www.riejournal.com/article_94178_1bd1b260d5efd921efbf29238133674e.pdfAyandegan Institute of Higher EducationInternational Journal of Research in Industrial Engineering2783-13378320190901Optimizing Supermarket Supply Chain using fuzzy AHP: A Study on Save 'n' Safe in Bangladesh2252429417710.22105/riej.2018.149536.1060ENAzad AbbasiDepartment of Industrial Engineering, Tehran University, Tehran, Iran.Journal Article20190523In today's business landscape, the concept of the supply chain has gained significant prominence. An efficient supply chain is essential for guiding a business in an organized manner. This importance extends to supermarkets, where effective supply chain management necessitates improved communication with suppliers, customers, and internal management. Each facet of the supply chain plays a pivotal role in its own right. This study aims to investigate the crucial factors within the supermarket supply chain, drawing insights from existing literature and input from supply chain experts. The objective is to construct a framework that prioritizes these factors, considering each facet of the supply chain and arranging them from most to least critical. This research focuses on the analysis of a specific supermarket in Bangladesh, namely Save 'n' Safe, utilizing the FAHP methodology, a Multi-Criteria Decision-Making (MCDM) tool, to identify the most influential factors. The findings highlight that inventory management, internal information sharing, and accurate demand forecasting are the key determinants for Save 'n' Safe, a supermarket. Furthermore, the paper offers recommendations to enhance the current supply chain situation. The implications of this study extend not only to other supermarkets but also to various retail and grocery stores.https://www.riejournal.com/article_94177_86006bb8ebd45fb7ce718837b80df4a3.pdfAyandegan Institute of Higher EducationInternational Journal of Research in Industrial Engineering2783-13378320190901An optimization model for cold chain food distribution2432539695210.22105/riej.2019.202178.1097ENA. K. GarsideDepartment of Industrial Engineering, Faculty of Technic, University of Muhammadiyah Malang, Indonesia.0000-0003-1692-0277Journal Article20190619Food product has a characteristic of continuous quality deterioration until the food is consumed. Cold chain distribution can improve the sustainability of the product quality but requires a more significant investment for storage facilities and vehicles as well as higher operation cost to control the temperature. This research focuses on a distribution problem faced by an ice cream distributor. In this paper, we developed a mixed-integer non-linear programming model to minimize the total cost, which consists of fixed cost, transportation cost of the vehicles, energy cost to keep the cold storage temperature, and inventory cost. The model considers the vehicle characteristics and hard time-windows for the distributor and all the stores. The implementation of this model demonstrates that the proposed route is able to reduce the total cost.https://www.riejournal.com/article_96952_99741663629e2652ff59f7cf563e0cf3.pdfAyandegan Institute of Higher EducationInternational Journal of Research in Industrial Engineering2783-13378320190901Calculation of fuzzy matrices determinant2542619695310.22105/riej.2019.202666.1098ENF. BabakordiDepartment of Mathematics, Faculty of Science, Gonbad Kavous University, Gonbad Kavous, Iran.N. A. Taghi-NezhadDepartment of Mathematics, Faculty of Science, Gonbad Kavous University, Gonbad Kavous, Iran.0000-0002-4568-0527Journal Article20190623Matrix and its determinant are two basic tools, which are important in financial, accounting, and economic affairs. Therefore, in this paper, a simple and effective method is proposed to obtain the determinant of fuzzy matrices. First, using arithmetic operations based on Transmission Average (TA),the second order fuzzy determinant is calculated.Then,Sarrus rule is defined to calculate third order fuzzy determinant. Finally, by defining minor of fuzzy matrix and ijth adjugate of the fuzzy matrix, nth order fuzzy determinant is calculated. The effectiveness and applicability of the proposed method are verified by solving some numerical examples.https://www.riejournal.com/article_96953_dd87d77c5812790a284a6ec9c8e22529.pdfAyandegan Institute of Higher EducationInternational Journal of Research in Industrial Engineering2783-13378320190901Some fixed point results involving a general LW-type cyclic mapping in complete b-metric-like spaces2622739418010.22105/riej.2019.195844.1093ENS. Q. WengIdeological and Political Foundation, SiChuan Sanhe College of Professionals, Hejiang, Luzhou, 646200, Sichuan, China.0000-0002-2994-6751Journal Article20190526In recent years, the research of the fixed point theorem is a hot topic all the time. In this paper, we propose the notion of new mapping, that is, a general LW-type cyclic mapping, in a complete b-metric-like spaces. Then, we obtain the existence and uniqueness theorem of its fixed point. Moreover, we give an example to illustrate the main results of this paper.https://www.riejournal.com/article_94180_9b07fd744930f2a14d13fc3e89a78e4d.pdfAyandegan Institute of Higher EducationInternational Journal of Research in Industrial Engineering2783-13378320190901A signed distance method for solving multi-objective transportation problems in fuzzy environment2742829417910.22105/riej.2019.193041.1091ENH. Abd El-Wahed KhalifaDepartment of Operations Research, Faculty of Graduate Studies for Statistical Research, Cairo University, Giza, Egypt.Journal Article20190606This paper aims to study the multi-objective transportation problem with fuzzy parameters. These fuzzy parameters represented as (α, β) interval-valued fuzzy numbers instead of the normal fuzzy numbers. Using the signed distance ranking, the problem converted into the corresponding crisp multi<strong><em>-</em></strong>objective transportation problem. Then, the solution method introduced by [8] for solving the problem is applied. This method provides the ideal and the set of all fuzzy (α, β) efficient solutions. The advantage of this method is more flexible than the standard multi-objective transportation problem, where it allows the decision maker to choose the (α, β) levels of fuzzy numbers he is willing. A numerical example to illustrate the utility, effectiveness, and applicability of the method is given.https://www.riejournal.com/article_94179_7d26c90796da3ea354f2dfdef0cc1dec.pdfAyandegan Institute of Higher EducationInternational Journal of Research in Industrial Engineering2783-13378320190901Evaluation of the efficiency by DEA a case study of hospital28329310076810.22105/riej.2020.211600.1106ENKh. GhaziyaniDepartment of Mathematics, Ayandegan Insttitute of Higher Education, Tonekabon, Iran.B. EjlalyDepartment of Engineering, Amirkabir University, Tehran, Iran.S. F. BagheriDepartment of Mathematics, Azad University, Branch Lahijan, Guilan, Iran.Journal Article20190512Data Envelopment Analysis (DEA) is a nonparametric technique used to determine the relative efficiency of Decision Making Units (DMUs). Results from DEA analysis yield important information regarding the optimal operating capabilities of each unit. This paper studies DEA to hospital sectors and identifies their rankings during a period of six years. Data for the study comes from a hospital in the North of Iran. This article compares the performance of different parts of the hospital over the years. It can also aid improve hospital performance.https://www.riejournal.com/article_100768_3310e9849f537d1c5ba5dc13afbf6816.pdf