Fuzzy inference systems and inventory allocation decisions: Exploring the impact of priority rules on total costs and service levels |
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| Affiliation: | 1. COPPEAD Graduate Business School, Federal University of Rio de Janeiro, Rua Paschoal Lemme, 355. 21949-900 Rio de Janeiro, Brazil;2. Crummer Graduate School of Business, Rollins College, 1000 Holt Ave. – 2722, Winter Park, Fl 32789, USA;3. Department of Mathematics, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran;4. Department of Business Administration, School of Business, Bangladesh Army International University of Science and Technology, Comilla-3501, Bangladesh;1. Decision Science Institute, School of Economics and Management, Fuzhou University, 2 Xueyuan road, Fuzhou 350116, China;2. School of Mathematics and Computer Science, Fuzhou University, 2 Xueyuan road, Fuzhou 350116, China;1. Departamento de Arquitectura y Tecnología de Sistemas Informáticos (DATSI), Universidad Politécnica de Madrid, Campus Montegancedo S/N, 28660 Boadilla del Monte, Spain;2. Informática El Corte Inglés, Engineering and Telecommunication Division, Travesía de Costa Brava, 28034 Madrid, Spain;3. Phedes Lab, Calle Los Cedros 4, 33423 Soto de Llanera, Asturias, Spain;1. Moscow Institute of Physics and Technology, Russia;2. Computing Centre of the Russian Academy of Sciences, Russia;1. Biomedical HPC Technology Research Center, Korean Institute of Science and Technology Information, Daejeon, Republic of Korea;2. Department of Computer Engineering, Gachon University, Seongnam-si, Gyeonggi-do, Republic of Korea;3. Department of Computer Science, Virginia Tech, Blacksburg, VA, USA;4. Department of Computer Science and Engineering, Incheon University, Incheon, Republic of Korea;1. University of Nova Gorica, Nova Gorica, Slovenia;2. Jo?ef Stefan Institute, Ljubljana, Slovenia;3. Temida d.o.o., Ljubljana, Slovenia |
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| Abstract: | Inventory allocation decisions in a distribution system concern issues such as how much and where stock should be assigned to orders in a supply chain. When the inventory level of an inventory point is lower than the total number of items ordered by lower echelons in the chain, the decision of how many items to allocate to each ``competing'' order must take into consideration the trade-off between cost and service level. This paper proposes a decision-support system that makes use of fuzzy logic to consider inventory carrying, shortage and ordering costs as well as transportation costs. The proposed system is compared through simulation with three other inventory allocation decision support models in terms of cost and service levels achieved. Conclusions are then drawn. |
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