An intermodal freight transport system for optimal supply chain logistics |
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| Institution: | 1. Department of Industrial Engineering and Management, Indian Institute of Technology, Kharagpur 721302, India;2. Department of Supply Chain Management, Broad School of Business, Michigan State University, 351 N. Business Complex, East Lansing, MI 48824, United States;1. German Aerospace Center (DLR) – Institute of Transport Research, Rutherfordstraße 2, 12489 Berlin, Germany;2. Technical University of Berlin, Straße des 17. Juni 135, 10623 Berlin, Germany;1. IDMEC, School of Business Administration, Polytechnical Institute of Setúbal, Portugal;2. Department of Maritime and Transport Technology, Delft University of Technology, The Netherlands;3. School of Business and Economics, Universidad Anáhuac México Norte, Mexico;4. IDMEC, Instituto Superior Técnico, Universidade de Lisboa, Portugal;1. Kuehne Logistics University, Hamburg 20457, Germany;2. Technology and Operations Management, Vlerick Business School, Leuven 3000, Belgium;3. Research Center for Operations Management, KU Leuven, Leuven 3000, Belgium;4. Supply Network Innovation Center, Strombeek-bever 1853, Belgium;1. Faculty of Business Administration, Memorial University, Canada;2. DeGroote School of Business, McMaster University, Canada |
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| Abstract: | Complexity in transport networks evokes the need for instant response to the changing dynamics and uncertainties in the upstream operations, where multiple modes of transport are often available, but rarely used in conjunction. This paper proposes a model for strategic transport planning involving a network wide intermodal transport system. The system determines the spatio-temporal states of road based freight networks (unimodal) and future traffic flow in definite time intervals. This information is processed to devise efficient scheduling plans by coordinating and connecting existing rail transport schedules to road based freight systems (intermodal). The traffic flow estimation is performed by kernel based support vector mechanisms while mixed integer programming (MIP) is used to optimize schedules for intermodal transport network by considering various costs and additional capacity constraints. The model has been successfully applied to an existing Fast Moving Consumer Goods (FMCG) distribution network in India with encouraging results. |
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| Keywords: | Spatio-temporal data mining Intermodal transport Support vector machines Mixed integer programming |
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