Publications       Rudy Negenborn
Full Professor
Director of Studies MSc TIL
Team & Themes

Title:Real-time container network planning based on post-optimality analysis using decision trees
Authors:B. van Riessen, R.R. Negenborn, R. Dekker

Conference:International Association of Maritime Economists Conference 2014 (IAME 2014)
Address:Norfolk, Virginia
Date:July 2014

Abstract:The transportation of containers between the port of Rotterdam and the hinterland is challenging, because of the increased congestion on inland road, water, and rail connections, while customers demand shorter and more reliable delivery times. Most inland transportation of containers is carried out by operators that are dedicated to specific routes and modes: barge, rail, or truck. A centralized optimisation method for determining the allocation of containers to inland transportation services has recently been proposed in the literature. Although in theory providing an optimal solution, such a centralized method cannot yet be applied in practice. For this reason, a method for rule-based decision support for allocating incoming orders directly is proposed in this paper. The set of rules in the decision support system is created using a two-step approach. The first step extracts information from a set of optimal planning solutions of the network transportation obtained off-line based on the recently proposed linear container allocation problem with time-restrictions. In the second step, the results of the first step are clustered using a decision tree generation algorithm. The decision tree can serve as a decision support for the human planner. A method based on decision rules is more comprehensible for human planners; it will therefore be more easily accepted for use in daily practice. As a case study, a week of incoming orders and execution of planned transportation for a transportation corridor from the port of Rotterdam is considered.

Reference:B. van Riessen, R.R. Negenborn, R. Dekker. Real-time container network planning based on post-optimality analysis using decision trees. In Proceedings of the International Association of Maritime Economists Conference 2014 (IAME 2014), Norfolk, Virginia, July 2014.
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