纹波扩散算法:一种求解混合时间窗多目标最短路径问题的新方法

IF 5 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Complex & Intelligent Systems Pub Date : 2023-11-14 DOI:10.1007/s40747-023-01260-8
Shilin Yu, Yuantao Song
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引用次数: 0

摘要

在应急管理中,应急物资和救援人员的运输调度可以看作是具有混合时间窗的多目标最短路径问题(MOSPPMTW),对时效性和有效性有很高的要求,但目前的求解算法不能同时兼顾求解精度和计算速度,这对应急路径决策非常不利。本文建立了匹配应急救援场景的MOSPPMTW,使物资和救援人员能够在最短的时间内以最小的成本同时到达应急现场。为了求解完全Pareto最优曲面,我们提出了一种纹波扩展算法(RSA),该算法通过进行纹波接力竞赛来获得Pareto最优路径解集,从而确定完全Pareto边界。提出的RSA算法不需要初始解和迭代,只需运行一次即可获得解集。进一步证明了RSA算法的最优性和时间复杂度,并进行了多组实例仿真实验。与其他算法相比,RSA在计算速度和解质量方面都有更好的表现。这种优势在大规模问题的计算中尤为明显。适用于各种紧急救灾场景,能够满足快速响应和时效性的要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Ripple spreading algorithm: a new method for solving multi-objective shortest path problems with mixed time windows

In emergency management, the transportation scheduling of emergency supplies and relief personnel can be regarded as the multi-objective shortest path problem with mixed time window (MOSPPMTW), which has high requirements for timeliness and effectiveness, but the current solution algorithms cannot simultaneously take into account the solution accuracy and computational speed, which is very unfavorable for emergency path decision-making. In this paper, we establish MOSPPMTW matching emergency rescue scenarios, which simultaneously enables the supplies and rescuers to arrive at the emergency scene as soon as possible in the shortest time and at the smallest cost. To solve the complete Pareto optimal surface, we present a ripple spreading algorithm (RSA), which determines the complete Pareto frontier by performing a ripple relay race to obtain the set of Pareto optimal path solutions. The proposed RSA algorithm does not require an initial solution and iterative iterations and only needs to be run once to obtain the solution set. Furthermore, we prove the optimality and time complexity of RSA and conduct multiple sets of example simulation experiments. Compared with other algorithms, RSA performs better in terms of computational speed and solution quality. The advantage is especially more obvious in the computation of large-scale problems. It is applicable to various emergency disaster relief scenarios and can meet the requirements of fast response and timeliness.

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来源期刊
Complex & Intelligent Systems
Complex & Intelligent Systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
9.60
自引率
10.30%
发文量
297
期刊介绍: Complex & Intelligent Systems aims to provide a forum for presenting and discussing novel approaches, tools and techniques meant for attaining a cross-fertilization between the broad fields of complex systems, computational simulation, and intelligent analytics and visualization. The transdisciplinary research that the journal focuses on will expand the boundaries of our understanding by investigating the principles and processes that underlie many of the most profound problems facing society today.
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