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A Study on Genetic Algorithms for the DARP Problem

机译:DARP问题的遗传算法研究

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摘要

This work presents the results on applying a genetic approach for solving the Dial-A-Ride Problem (DARP). The problem consists of assigning and scheduling a set of user transport requests to a fleet of available vehicles in the most efficient way according to a given objective function. The literature offers different heuristics for solving DARP, a well known NP-hard problem, which range from traditional insertion and clustering algorithms to soft computing techniques. On the other hand, the approach through Genetic Algorithms (GA) has been experienced in problems of combinatorial optimization. We present our experience and results of a study to develop and test different GAs in the aim of finding an appropriate encoding and configuration, specifically for the DARP problem with time windows.
机译:这项工作提出了应用遗传方法解决“ A盘搭车”问题(DARP)的结果。问题包括根据给定的目标函数以最有效的方式向一组可用车辆分配和调度一组用户运输请求。文献提供了不同的启发式方法来解决DARP(众所周知的NP难题),其范围从传统的插入和聚类算法到软计算技术。另一方面,通过遗传算法(GA)的方法已在组合优化问题中经历过。我们将介绍我们的经验和开发和测试不同GA的研究结果,以找到合适的编码和配置,特别是针对带有时间窗的DARP问题。

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