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A column generation approach for determining optimal fleet mix, schedules, and transshipment facility locations for a vessel transportation problem

机译:确定船舶运输问题的最佳船队组合,时间表和转运设施位置的列生成方法

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This paper presents a column generation approach for a storage replenishment transportation-scheduling problem. The problem is concerned with determining an optimal combination of multiple-vessel schedules to transport a product from multiple sources to different destinations based on demand and storage information at the destinations, along with cost-effective optimal strategic locations for temporary transshipment storage facilities. Such problems are faced by oil/trucking companies that own a fleet of vessels (oil tankers or trucks) and have the option of chartering additional vessels to transport a product (crude oil or gasoline) to customers (storage facilities or gas stations) based on agreed upon contracts. An integer-programing model that determines a minimum-cost operation of vessels based on implicitly representing feasible shipping schedules is developed in this paper. Due to the moderate number of constraints but an overwhelming number of columns in the model, a column generation approach is devised to solve the continuous relaxation of the model, which is then coordinated with a sequential fixing heuristic in order to solve the discrete problem. Computational results are presented for a range of test problems to demonstrate the efficacy of the proposed approach.
机译:本文提出了一种针对存储补货运输计划问题的列生成方法。该问题涉及基于目的地的需求和存储信息以及用于临时转运存储设施的成本有效的最佳战略位置,确定将多个产品计划从多个来源运输到不同目的地的多船时间表的最佳组合。拥有船队(油轮或卡车)并且可以选择租用其他船只将产品(原油或汽油)运输到客户(仓储设施或加油站)的石油/货运公司面临此类问题。同意合同。本文开发了一种整数编程模型,该模型基于隐式表示可行的运输计划来确定船舶的最低成本。由于模型中约束的数量适中,但列的数量过多,因此设计了一种列生成方法来解决模型的连续松弛问题,然后将其与顺序固定启发式算法相协调,以解决离散问题。给出了一系列测试问题的计算结果,以证明所提出方法的有效性。

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