Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/34778
Title: Operational model for empty container repositioning
Authors: LONG YIN
Keywords: Empty Container Repositioning, Stochastic Programming, Sample Average Approximation, Scenario Decomposition, Progressive Hedging, Supersaturated Desig
Issue Date: 24-Apr-2012
Source: LONG YIN (2012-04-24). Operational model for empty container repositioning. ScholarBank@NUS Repository.
Abstract: Empty Container Repositioning (ECR) has become a crucial issue due to the global trade imbalance between different regions. The operational ECR problem is motivated by a real situation faced by an international shipping company. We first formulate the ECR problem as a deterministic time space network model under rolling horizon policy to cope with the dynamically changing environment in container shipping industry. Considering the uncertainties in maritime container transportation, the second part of our work is to extend the proposed deterministic model to a two-stage stochastic model in dealing with the uncertainties in ECR. The Sample Average Approximation (SAA) method is applied to solve the stochastic ECR problem with a large number of scenarios. To solve the large scale SAA problem, scenario decomposition is applied. Algorithms based on the progressive hedging strategy are proposed to solve the stochastic ECR problem. Moreover, new sampling methods which construct the Latin hypercube design based on supersaturated design are proposed to enhance the performance of the SAA method.
URI: http://scholarbank.nus.edu.sg/handle/10635/34778
Appears in Collections:Ph.D Theses (Open)

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