Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/30300
Title: Liner ship fleet planning with uncertain container shipment demand
Authors: WANG TING SONG
Keywords: liner ship fleet planning,container shipment demand uncertainty,stochastic programming,integer programming
Issue Date: 14-Jul-2011
Source: WANG TING SONG (2011-07-14). Liner ship fleet planning with uncertain container shipment demand. ScholarBank@NUS Repository.
Abstract: The liner ship fleet planning helps to create cost-effective plans for a liner shipping company to operate and upgrade its liner ship fleet and seizing market share in an intensely competitive container shipping market. The container shipment demand is affected by some unpredictable and uncontrollable factors, which indicates that such plans have to be made on the basis of uncertain demand. However, methodologies used by previous researchers are inappropriate here because they make the assumption that container shipment demand is deterministic. Hence, new methodologies are required. This thesis seeks to meet this requirement by proposing new mathematical models and solution algorithms for liner ship fleet planning (LSFP) problems with container shipment demand uncertainty. This thesis first studies short-term LSFP problem with uncertain container shipment demand and formulates it as a chance-constrained programming (CCP) model. However, the CCP model does not allow container transshipment, which is widely used in liner shipping. Therefore, a two-stage stochastic integer programming (2SSIP) model, with the objective of maximizing expected profit, is proposed for the short-term LSFP problem with container transshipment and uncertain container shipment demand. The model only considers the expected value; variance (or risk), which is also an issue of high concern to the decision-maker, is not taken into account. Therefore, a robust optimization model (ROM), in which both expected value and variance are considered simultaneously for the short-term LSFP problem, is proposed. The last part of this thesis studies the long-term/multi-period LSFP problem with container transshipment and uncertain demand. The procedure for multi-period LSFP is interpreted as a decision tree and formulated as a multi-period stochastic programming model comprising a sequence of interrelated two-stage stochastic programming models developed for each single period. For each mathematical model, a corresponding solution algorithm is proposed and its efficiency is tested by numerical examples.
URI: http://scholarbank.nus.edu.sg/handle/10635/30300
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