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Independent travel recommendation algorithm based on analytical hierarchy process and simulated annealing for professional tourist

机译:基于分析层次工艺的独立旅游推荐算法及专业游客模拟退火

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摘要

Independent travelers, especially professional independent travelers, tend to plan their trip schedules according to their interests, preferred hotels, landmarks they wish to visit, budgets, time availability and various other factors. Hence, travel schedule planning is valuable for satisfying the unique needs of each traveler. In this paper, we propose an algorithm for independent travel recommendation, consisting of three steps. Firstly, landmarks in the destination are selected under the specific constraints, which is modeled as a 0-1 knapsack problem. Then, the landmarks will be evaluated comprehensively using AHP (Analytic Hierarchy Process) model, and the greedy simulated annealing algorithm is adopted to select the best landmarks with high evaluation scores. Next, with AHP-decision model, a most reasonable free line to the tourist destination is selected from multiple candidates. Lastly, the path planning among the landmarks is abstracted as a TSP (Travelling Sales Problem) problem, and the simulated annealing algorithm based on roulette wheel selection is adopted to solve it. Through simulation experiments, by comparing with package tour from the aspects of landmark selection, valid sightseeing time ratio, valid sightseeing consumption ratio and the tourist satisfaction, the proposed algorithm is evaluated and analyzed. Simulation results illustrate the feasibility and rationality of our approach, which can be used as an effective reference deciding individualized travel schedules and trip planning.
机译:独立旅行者,特别是专业的独立旅行者,倾向于根据他们的兴趣,首选酒店,他们希望访问的地标,预算,时间可用性和各种其他因素来规划旅行时间表。因此,旅行时间表规划对于满足每个旅行者的独特需求是有价值的。在本文中,我们提出了一种独立旅行推荐算法,包括三个步骤。首先,在特定约束下选择目的地中的地标,该特定约束被建模为0-1背包问题。然后,使用AHP(分析层次处理)模型全面评估该地标,采用贪婪模拟退火算法来选择具有高评价分数的最佳地标。接下来,使用AHP决策模型,从多个候选中选择到旅游目的地的最合理的释放线。最后,地标之间的路径规划被提取为TSP(行驶销售问题)问题,采用基于轮盘赌选择选择的模拟退火算法来解决。通过模拟实验,通过与地标选择,有效的观光时间比,有效观光消费比和旅游满意度的方面进行比较,评估和分析了所提出的算法。仿真结果说明了我们方法的可行性和合理性,可用作决定个性化旅行时间表和旅行计划的有效参考。

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