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A methodology to support decision-making on sugar distribution for export channel: A case study of Thai sugar industry
Institution:1. CSDC, Department of Physics, University of Florence, via G. Sansone 1, Sesto Fiorentino, Florence, 50019, Italy;2. Institute for Complex Systems and Mathematical Biology, University of Aberdeen, Meston Building, Meston Walk, Aberdeen, AB24 3UE, United Kingdom;1. Stanford University Human Immune Monitoring Center, Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA;2. Stanford University School of Medicine, 291 Campus Drive, Stanford, CA 94305, USA;3. VA Palo Alto Healthcare System, 3801 Miranda Avenue, Palo Alto, CA 94304, USA;1. Institute of Transport and Logistics (ITLS), University of Sydney Business School, NSW 2006 Australia
Abstract:Supply chain research can lead to an increase in efficiency, business integration, responsiveness and ultimately market competitiveness. In the sugar industry, such research has expanded rapidly over the past two decades, and has been motivated by low world sugar prices and rising costs of production. However, in the present competitive business environment, a more customer-driven and holistic approach to supply chain management is required. This study focuses on warehouse and distribution management for the export channel of Thai sugar industry. The aim is to suggest the best inventory position and transportation route in the distribution system based on Genetic Algorithm (GA). It provides a systematic and flexible framework to solve the problem of cost minimization of sugar transport from the mills to seaports. The results demonstrate that the tool is not only useful for minimizing the cost, but also for managing sugar warehousing, distribution route and seaport exporting. While the focus of this paper is on sugar supply chain, much of the information is relevant to distribution management of other agricultural commodities as well.
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