A Water Wave Optimization Algorithm for Order Selection and Delivery Path Optimization for Takeaway Deliverymen

Jia-Yu Wu, Min-Xia Zhang, Xue Wu, Yujun Zheng
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引用次数: 3

Abstract

Over the last years, the food delivery market has seen significant growth and provide a lot of jobs for deliverymen. The revenue of a takeaway deliveryman depends on not only reasonable order taking but also efficient delivery path planning. However, it is challenging to select among a large number of candidate orders and plan an efficient route passing all involved pickup points and service points. In this paper, we present a problem integrating order selection and delivery path optimization for takeaway deliverymen. The objective is to maximize the revenue per unit time subject to overtime penalty and high-workload reward. To efficiently solve this problem, we propose a hybrid intelligent algorithm, which adapts the water wave optimization (WWO) metaheuristic to evolve solutions to the main order selection problem and employs tabu search to optimize the path for each order selection solution. Experimental results on test instances demonstrate the performance advantages of the proposed algorithm compared to a set of popular metaheuristic optimization algorithms.
基于水波优化算法的外卖送餐员选单与送餐路径优化
在过去的几年里,外卖市场有了显著的增长,并为外卖员提供了很多工作。外卖快递员的收入不仅取决于合理的接单,还取决于高效的配送路径规划。然而,在大量的候选订单中进行选择并规划一条通过所有涉及的取件点和服务点的有效路线是一项挑战。本文针对外卖配送员提出了一个整合订单选择和配送路径优化的问题。目标是在加班和高工作量奖励的前提下,使单位时间的收益最大化。为了有效地解决这一问题,我们提出了一种混合智能算法,该算法采用水波优化(WWO)元启发式方法来进化主阶选择问题的解,并采用禁忌搜索来优化每个阶选择解的路径。在测试实例上的实验结果表明,与一组常用的元启发式优化算法相比,该算法具有性能优势。
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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