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Decentralized Evolutionary Optimization Approach to the p-Median Problem

机译:p中值问题的分散进化优化方法

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摘要

The facility location problem also known as p-median problem concerns the positioning of facilities such as bus-stops, broadcasting stations or supply stations in general. The objective is to minimize the weighted distance between demand points (or customers) and facilities. In general there is a trend towards networked and distributed organizations and their systems, complicating the design, construction and maintenance of distributed facilities as information is scattered among participants while no global view exists. There is a need to investigate distributed approaches to the p-median problem. This paper contributes to research on location problems by proposing an agent oriented decentralized evolutionary computation (EC) approach that exploits the flow of money or energy in order to realize distributed optimization. Our approach uses local operators for reproduction like mutation, recombination and selection finally regulated by market mechanisms. This paper presents two general outcomes of our model: how adaptation occurs in the number and strategies of agents leading to an improvement at the system level. The novelty of this approach lies in the biology-inspired bottom-up adaptation method for inherent distributed problems. It is applied to the uncapacitated p-median problem but is also intended to be general for a wide variety of problems and domains, e.g. wireless sensor networks.
机译:设施位置问题也称为p中位数问题,通常涉及诸如公共汽车站,广播站或供应站之类的设施的定位。目的是最小化需求点(或客户)和设施之间的加权距离。通常,趋势是网络化和分布式组织及其系统,这使得分布式设施的设计,构建和维护变得复杂,因为信息分散在参与者之间,而没有全局视野。有必要研究p中值问题的分布式方法。本文通过提出一种面向代理的分散式进化计算(EC)方法来为选址问题做出贡献,该方法利用资金或能源流来实现分布式优化。我们的方法使用本地运营商进行复制,如突变,重组和选择,这些最终受市场机制约束。本文介绍了我们模型的两个一般结果:适应如何在代理的数量和策略上发生,从而导致系统级别的改进。这种方法的新颖之处在于针对固有的分布式问题的生物学启发的自下而上的适应方法。它适用于无能力的p中位数问题,但也打算广泛用于各种问题和领域,例如无线传感器网络。

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