Exploring the Use of Fuzzy Inference System in Order Sizing Decisions
DOI:
https://doi.org/10.23055/ijietap.2019.26.4.4528Keywords:
Order Sizing, Fuzzy Inference System, Stochastic Dynamic Programming, 2D Fuzzy Monte Carlo Simulation, Stock ControlAbstract
Key to the problem of stock management is the uncertainty of product demand. What is the best way to include the consideration of demand uncertainty in models that are both effective and applicable to the day-to-day complexities facing managers? This paper presents two innovative ways of considering demand uncertainty in stock control. The first approaches uncertainty as a stochastic phenomenon, which we address by using a Stochastic Dynamic Programming (SDP) model. The second approaches demand uncertainty as a fuzzy-type phenomenon, which we address using Fuzzy Inference System(FIS). Our focus is to explore the application of Fuzzy Inference System to a classic problem of stock control: the definition of order sizes. For a given demand scenario, we evaluate the two approaches by calculating their total cost’s present value and by comparing their cost performance. The cost evaluation method used was a Two-Dimensional Fuzzy Monte Carlo Simulation, in which 10,540 demand scenarios were analyzed. Our results show that the SDP model results in lower total costs compared to the FIS model. We also found out that the distributions of FIS decisions were similar to the SDP and that costs varied up to 40% from the optimal value. Thus, in a situation where it is either impossible or unfeasible to solve the problem using SDP, Fuzzy Inference Systems can be utilized as a relatively simple and effective alternative.Author Biography
Peter Wanke, COPPEAD graduate Business School
Visiting scholar at Ohio State University/ Department of Marketing and Logistics, Peter Wanke has his Ph.D. in Industrial Engineering from COPPE/ Universidade Federal do Rio de Janeiro (UFRJ). Professor Wanke has his Master’s Degree in Industrial Engineering from COPPE/ UFRJ and he is graduated in Industrial Engineering from the School of Engineering/ UFRJ.
A recognized expert in logistics and supply chain management, Professor Wanke is currently Deputy Director of Doctoral and Research at COPPEAD Business School/ UFRJ, Coordinator of a research center in logistics, infrastructure and management called CELIG, and Associate Professor at COPPEAD Business School.
He is engaged in teaching, research, and consultancy activities in areas such as facility location, simulation of logistics and transportation systems, demand forecasting and planning, inventory management in supply chains, efficiency analysis of business units, and logistics strategy.
His over than 60 papers are published in conferences, magazines, and national and international impact factor scientific journals, such as International Journal of Physical Distribution & Logistics Management, International Journal of Operations & Production Management, International Journal of Production Economics, Transportation Research Part E, International Journal of Simulation & Process Modelling, Transport Reviews, Measurement, Biomass and Bioenergy, International Journal of Logistics Research and Applications, Health Care Management Science, Expert Systems with Applications, Journal of Air Transport Management, Transport Policy, Applied Economics, Socio-Economic Planning Sciences, and International Journal of Logistics Economics and Globalisation.
He is author of several books, including “Gestão de Estoques na Cadeia de Suprimento – Decisões e Modelos Quantitativos”, “Logística e Transporte de Cargas no Brasil: Produtividade e Eficiência no Século XXI”, “Estratégia Logística em Empresas Brasileiras – um Enfoque em Produtos Acabados”, “Logística para MBA Executivo em 12 Lições”, “Gerência de Operações – Uma Abordagem Logística”, and “Logística para Micro e Pequenas Empresas”.
Professor Wanke is also one of the organizers of these books: “Logística Empresarial – A Perspectiva Brasileira”, “Previsão de Vendas – Processos Organizacionais & Métodos Quantitativos”, “Logística e Gerenciamento da Cadeia de Suprimentos: Planejamento do Fluxo de Produtos e dos Recursos”, “Introdução ao Planejamento de Redes Logísticas: Aplicações em AIMMS”, and “Introdução ao Planejamento da Infraestrutura e Operações Portuárias: Aplicações de Pesquisa Operacional”.
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