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首页> 外文期刊>Journal of intelligent & fuzzy systems: Applications in Engineering and Technology >Solving a novel multi-objective uncapacitated hub location problemby five meta-heuristics
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Solving a novel multi-objective uncapacitated hub location problemby five meta-heuristics

机译:用五种元启发式方法解决新颖的多目标无能力枢纽定位问题

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摘要

This paper deals with three characteristics of transportation costs, crowding and traffic costs, and the costs of hub installation. The main aim of this paper is to define the independent cost function in order to connect to the crowding rate and incurred cost in an exponential way not considered in the literature directly. In this function, the independent variable is the crowding and traffic rate input, and the output is the cost incurred. However, involving three separate objective functions namely total cost, congestion and hub installation costs are not considered up to now. Also, considering the contrast among three foregoing costs, each function is considered independently. Due to the NP-hardness of this kind of problem to solve this multi-objective mathematical model, at first we devised an efficient approach to navigate through the feasible solution space iteratively without using penalty function. To solve our developed multi-objective mathematical model we propose five multi-objective meta-heuristic algorithms, namely 1) NSGA-II with an elitism solution, 2) NSGA-II without an elitism solution, 3) NRGA with an elitism solution, 4) NRGA without an elitism solution, and 5) MOPSO. Finally, three criteria are used to compare the related results obtained by these five algorithms.
机译:本文讨论了运输成本,拥挤和交通成本以及集线器安装成本的三个特征。本文的主要目的是定义独立的成本函数,以便以直接在文献中未考虑的指数方式与拥挤率和产生的成本联系起来。在此函数中,自变量是拥挤和交通费率输入,而输出是所产生的成本。但是,到目前为止,尚未考虑涉及三个独立的目标功能,即总成本,拥塞和集线器安装成本。而且,考虑到前述三个成本之间的对比,每个功能被独立考虑。由于此类问题的NP难性,无法解决该多目标数学模型,因此,我们首先设计了一种有效的方法来迭代导航可行解空间而无需使用惩罚函数。为了解决我们开发的多目标数学模型,我们提出了五种多目标元启发式算法,即1)具有精英解决方案的NSGA-II,2)没有精英解决方案的NSGA-II,3)具有精英解决方案的NRGA,4 )没有精英解决方案的NRGA,以及5)MOPSO。最后,使用三个标准来比较通过这五个算法获得的相关结果。

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