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A decision model for berth allocation under uncertainty

机译:不确定条件下泊位分配决策模型

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摘要

This paper studies the berth allocation problem (BAP) under uncertain arrival time or operation time of vessels. It does not only concern the proactive strategy to develop an initial schedule that incorporates a degree of anticipation of uncertainty during the schedule's execution, but also studies the reactive recovery strategy which adjusts the initial schedule to handle realistic scenarios with minimum penalty cost of deviating from the initial schedule. A two-stage decision model is developed for the BAP under uncertainties. Moreover, a meta-heuristic approach is proposed for solving the above problem in large-scale realistic environments. Numerical experiments are conducted to validate the effectiveness and efficiency of the proposed method.
机译:本文研究了不确定到达时间或船只运行时间下的泊位分配问题(BAP)。它不仅涉及制定初始计划的积极策略,该初始计划在执行计划过程中结合了一定程度的不确定性,而且还研究了被动恢复策略,该策略可以调整初始计划以处理实际情况,而使违规成本最小化。初始时间表。针对不确定性,针对BAP建立了两阶段决策模型。此外,提出了一种元启发式方法来解决大规模现实环境中的上述问题。通过数值实验验证了该方法的有效性和有效性。

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