Combining linear programming and automated planning to solve intermodal transportation problems

When dealing with transportation problems Operational Research (OR), and related areas as Artificial Intelligence (AI), have focused mostly on uni-modal transport problems. Due to the current existence of bigger international logistics companies, transportation problems are becoming increasingly more complex. One of the complexities arises from the use of intermodal transportation. Intermodal transportation reflects the combination of at least two modes of transport in a single transport chain, without a change of container for the goods. In this paper, a new hybrid approach is described which addresses complex intermodal transport problems. It combines OR techniques with AI search methods in order to obtain good quality solutions, by exploiting the benefits of both kinds of techniques. The solution has been applied to a real world problem from one of the largest spanish companies using intermodal transportation, Acciona Transmediterranea Cargo.

[1]  David Pisinger,et al.  An Adaptive Large Neighborhood Search Heuristic for the Pickup and Delivery Problem with Time Windows , 2006, Transp. Sci..

[2]  Paolo Traverso,et al.  Automated Planning: Theory & Practice , 2004 .

[3]  Gerhard F. Post,et al.  Generating price‐effective intermodal routes , 2011 .

[4]  Henry A. Kautz,et al.  State-space Planning by Integer Optimization , 1999, AAAI/IAAI.

[5]  Kap-Hwan Kim,et al.  intermodal transportation , 2022, The Fairchild Books Dictionary of Fashion.

[6]  Walter Ukovich,et al.  Minimizing fleet operating costs for a container transportation company , 2006, Eur. J. Oper. Res..

[7]  Daniel Borrajo,et al.  Using Cases Utility for Heuristic Planning Improvement , 2007, ICCBR.

[8]  Warren B. Powell,et al.  Implementing Real-Time Optimization Models: A Case Application From The Motor Carrier Industry , 2002, Oper. Res..

[9]  Stefan Bock,et al.  Production , Manufacturing and Logistics Real-time control of freight forwarder transportation networks by integrating multimodal transport chains , 2009 .

[10]  Akio Imai,et al.  A Lagrangian relaxation-based heuristic for the vehicle routing with full container load , 2007, Eur. J. Oper. Res..

[11]  Miguel A. Salido,et al.  Mathematical Solutions for Solving Periodic Railway Transportation , 2009 .

[12]  Lars Mönch,et al.  A methodology to solve large-scale cooperative transportation planning problems , 2012, Eur. J. Oper. Res..

[13]  Akio Imai,et al.  Multi-port vs. Hub-and-Spoke port calls by containerships , 2009 .

[14]  Vedat Verter,et al.  A bi-objective model for planning and managing rail-truck intermodal transportation of hazardous materials , 2012 .

[15]  Tom Bylander.  A Linear Programming Heuristic for Optimal Planning , 1997, AAAI/IAAI.

[16]  Daniel Borrajo,et al.  Solving Clustered Oversubscription Problems for Planning e-Courses , 2009 .

[17]  Maria Fox,et al.  PDDL2.1: An Extension to PDDL for Expressing Temporal Planning Domains , 2003, J. Artif. Intell. Res..

[18]  Jörg Hoffmann,et al.  FF: The Fast-Forward Planning System , 2001, AI Mag..

[19]  Gerrit K. Janssens,et al.  Planning Problems in Intermodal Freight Transport: Accomplishments and Prospects , 2008 .

[20]  Peter J. Stuckey,et al.  MiniZinc: Towards a Standard CP Modelling Language , 2007, CP.

[21]  Tsung-Sheng Chang,et al.  Best routes selection in international intermodal networks , 2008, Comput. Oper. Res..

[22]  Ivan Serina,et al.  Planning Through Stochastic Local Search and Temporal Action Graphs in LPG , 2003, J. Artif. Intell. Res..

[23]  Yixin Chen,et al.  SGPlan: Subgoal Partitioning and Resolution in Planning , 2004 .