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首页> 外文期刊>Journal of heuristics >A slope scaling/Lagrangean perturbation heuristic with long-term memory for multicommodity capacitated fixed-charge network design
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A slope scaling/Lagrangean perturbation heuristic with long-term memory for multicommodity capacitated fixed-charge network design

机译:具有用于多功能电容固定电荷网络设计的长期存储器的斜率缩放/拉格朗造扰动启发式

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摘要

This paper describes a slope scaling heuristic for solving the multicomodity capacitated fixed-charge network design problem. The heuristic integrates a Lagrangean perturbation scheme and intensification/diversification mechanisms based on a long-term memory. Although the impact of the Lagrangean perturbation mechanism on the performance of the method is minor, the intensification/diversification components of the algorithm are essential for the approach to achieve good performance. The computational results on a large set of randomly generated instances from the literature show that the proposed method is competitive with the best known heuristic approaches for the problem. Moreover, it generally provides better solutions on larger, more difficult, instances.
机译:本文介绍了一种倾斜缩放启发式,用于解决多种电容电容固定电荷网络设计问题。 启发式基于长期记忆集成了拉格朗文扰动方案和强化/多样化机制。 虽然Lagrangean扰动机制对方法的性能的影响很小,但算法的强化/多样化组件对于实现良好性能的方法至关重要。 来自文献的一大集随机生成的实例的计算结果表明,该方法具有竞争力的问题,具有最着名的启发式方法。 此外,它通常提供更好的解决方案,更大,更困难的情况。

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