首页> 外文会议>International Conference on Sensors Models in Remote Sensing Photogrammetry >A NEW MULTIMODAL MULTI-CRITERIA ROUTE PLANNING MODEL BY INTEGRATING A FUZZY-AHP WEIGHTING METHOD AND A SIMULATED ANNEALING ALGORITHM
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A NEW MULTIMODAL MULTI-CRITERIA ROUTE PLANNING MODEL BY INTEGRATING A FUZZY-AHP WEIGHTING METHOD AND A SIMULATED ANNEALING ALGORITHM

机译:一种新的多模多标准路线规划模型,通过集模加权方法和模拟退火算法

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A multimodal multi-criteria route planning (MMRP) system provides an optimal multimodal route from an origin point to a destination point considering two or more criteria in a way this route can be a combination of public and private transportation modes. In this paper, the simulate annealing (SA) and the fuzzy analytical hierarchy process (fuzzy AHP) were combined in order to find this route. In this regard, firstly, the effective criteria that are significant for users in their trip were determined. Then the weight of each criterion was calculated using the fuzzy AHP weighting method. The most important characteristic of this weighting method is the use of fuzzy numbers that aids the users to consider their uncertainty in pairwise comparison of criteria. After determining the criteria weights, the proposed SA algorithm were used for determining an optimal route from an origin to a destination. One of the most important problems in a meta-heuristic algorithm is trapping in local minima. In this study, five transportation modes, including subway, bus rapid transit (BRT), taxi, walking, and bus were considered for moving between nodes. Also, the fare, the time, the user's bother, and the length of the path were considered as effective criteria for solving the problem. The proposed model was implemented in an area in centre of Tehran in a GUI MATLAB programming language. The results showed a high efficiency and speed of the proposed algorithm that support our analyses.
机译:多模式多标准路线规划(MMRP)系统提供从原始点到目的点的最佳多模式路由,考虑到这条路线可以是公共和私人运输模式的组合的方式考虑两个或更多个标准。在本文中,组合模拟退火(SA)和模糊分析等级过程(模糊AHP)以找到这条路线。在这方面,首先,确定了对其旅行中有重大的有效标准。然后使用模糊AHP加权方法计算每个标准的重量。这种加权方法最重要的特征是使用模糊数,使用户能够考虑其对标准的成对比较的不确定性。在确定标准权重之后,所提出的SA算法用于确定从原点到目的地的最佳路由。元启发式算法中最重要的问题之一是在局部最小值中捕获。在本研究中,在节点之间移动了五种运输模式,包括地铁,总线快速传输(BRT),出租车,行走和公共汽车。此外,票价,时间,用户的烦恼和路径的长度被认为是解决问题的有效标准。拟议的模型是在GUI Matlab编程语言的德黑兰中心的一个地区实施。结果显示了支持我们分析的所提出的算法的高效率和速度。

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