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A firefly algorithm for the environmental prize-collecting vehicle routing problem

机译:一种萤火虫算法为环境筹码收集车辆路径问题

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摘要

In the present research, a new variant of the Vehicle Routing Problem (VRP), the Environmental Prize-Collecting Vehicle Routing Problem (E-PCVRP), is introduced. The E-PCVRP is a selective routing problem that focuses on the maximization of the aggregated prize values collected from the visited nodes while minimizing the fixed and variable cost of the formed routes. In terms of variable cost, the CO2 emissions of the vehicles performing the routes are considered as a load-distance function. The presented solution approach is based on the Firefly Algorithm (FA). The FA is an optimization algorithm, designed for the solution of continuous problems, while the proposed E-PCVRP, requires a discrete solution approach. Addressing the above discrepancy, the Firefly Algorithm based on Coordinates (FAC) is introduced, which incorporates the proposed "Coordinates Related" (CR) encoding/decoding process in the original FA scheme. The CR is a novel process that allows for algorithms designed for continuous optimization to by employed in the solution of discrete problems, such as the VRP. Specifically, the CR utilizes auxiliary vectors for solution representation, containing the Cartesian coordinates of each node, that allows for the original movement equation of the FA to be applied directly. The effectiveness of the FAC algorithm is showed over computational experiments and statistical analysis, in comparison to the performance of other bio-inspired algorithms and a mathematical solver.
机译:在本研究中,介绍了车辆路由问题(VRP)的新变种​​,环境奖励车辆路由问题(E-PCVRP)。 E-PCVRP是一个选择性路由问题,专注于从访问的节点收集的聚合奖品值的最大化,同时最小化所形成的路由的固定和可变成本。就可变成本而言,执行路线的车辆的二氧化碳排放被认为是负载距离功能。呈现的解决方案方法基于萤火虫算法(FA)。该FA是一种优化算法,用于解决连续问题的解决方案,而提出的E-PCVRP则需要采用离散解决方案方法。解决上述差异,引入了基于坐标(FAC)的萤火虫算法,其包括原始FA方案中所提出的“坐标相关”(CR)编码/解码过程。 CR是一种新的过程,允许设计用于连续优化的算法,通过在离散问题的解决方案中,例如VRP。具体地,CR利用用于解决方案表示的辅助矢量,其中包含每个节点的笛卡尔坐标,其允许直接应用FA的原始移动方程。与其他生物启发算法和数学求解器的性能相比,在计算实验和统计分析中显示了FAC算法的有效性。

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