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Automatic Planning of Multiple Itineraries: A Niching Genetic Evolution Approach

机译:多行程的自动规划:一种占状遗传演化方法

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摘要

Automatic itinerary planning is a crucial and challenging issue in tourism. This paper proposes a novel automatic planning method to suggest multiple itineraries that satisfy the specific demands of tourists. First, a multiple-itinerary planning model is developed, which provides three customized goals for a tourist to choose and supports generating multiple $D$ -day trips. The model makes fewer assumptions than the literature works did, while it provides more flexibility to the tourists. Then, based on the multiple-itinerary planning model, we design a niching genetic evolution approach to accomplish the automatic itinerary planning task. The genetic evolution approach guarantees a high search efficiency, while the niching strategy facilitates maintaining the population diversity. Consequently, the resultant algorithm can finally provide a number of diverse and superior solutions. Experimental results on real-world datasets show that our proposed algorithm not only outperforms state-of-the-art methods in considering different user-specified goals, but it is also capable of generating a set of diverse itineraries for the tourist to select. Additional experiments further verify the scalability of the proposed algorithm in terms of the problem size and the optimization objective.
机译:自动行程规划是旅游业的至关重要和挑战性问题。本文提出了一种新的自动规划方法,提出了满足游客特定需求的多种行程。首先,开发了一种多行程规划模型,为旅游提供了三个自定义目标,可供选择和支持生成多个$ D -day TRIPS。该模型的假设比文学作品更少,而它为游客提供了更大的灵活性。然后,基于多行程规划模型,我们设计了一种努力遗传演化方法来实现自动行程规划任务。遗传演化方法保证了高的搜索效率,而职能策略有助于维持人口多样性。因此,所得到的算法最终可以提供许多不同的解决方案。实验结果对现实世界数据集显示,我们的算法不仅优于考虑不同的用户指定的目标而优于最先进的方法,而且还能够为游客生成一组不同的行程来选择。附加实验进一步验证了在问题大小和优化目标方面所提出的算法的可扩展性。

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    South China Univ Technol Sch Comp Sci & Engn Guangzhou 510006 Peoples R China|South China Univ Technol Guangdong Prov Key Lab Computat Intelligence & Cy Guangzhou 510006 Peoples R China;

    South China Univ Technol Sch Comp Sci & Engn Guangzhou 510006 Peoples R China|South China Univ Technol Guangdong Prov Key Lab Computat Intelligence & Cy Guangzhou 510006 Peoples R China;

    Dongguan Univ Technol Sch Comp Sci & Technol Dongguan 523808 Peoples R China;

    South China Univ Technol Sch Comp Sci & Engn Guangzhou 510006 Peoples R China|South China Univ Technol Guangdong Prov Key Lab Computat Intelligence & Cy Guangzhou 510006 Peoples R China;

    Victoria Univ Melbourne Vic 8001 Australia;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    D-day itinerary; genetic algorithm; itinerary planning; multiple itineraries; niching strategy;

    机译:D-Day行程;遗传算法;行程规划;多行程;努力策略;

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