A*-guided heuristic for a multi-objective bus passenger Trip Planning Problem

被引:3
|
作者
Fournier, Sylvain M. R. [1 ]
Hulse, Eduardo Otte [1 ]
Pinheiro, Eder Vasco [1 ]
机构
[1] WPLEX Software Ltda, Rod SC 401,8600 Bloco 5,Sala 101, BR-88050000 Florianopolis, SC, Brazil
关键词
Trip Planning Problem; Pareto dominance; A* algorithm;
D O I
10.1007/s12469-019-00204-1
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
The Bus Passenger Trip Planning Problem is the decision problem the bus passenger faces when he has to move around the city using the bus network: how and when can he reach his destination? Or possibly: given a fixed time to get to the destination, what should be his departure time? We show that both questions are computationally equivalent and can be answered using an A*-guided and Pareto dominance-based heuristic. The A* procedure drives the search estimating the arrival time at the target node, even in intermediate nodes. Dominance is triggered each time a new label is generated, in order to prune out labels defining subpaths with high values for the objectives we focus on: arrival time at destination, number of transfers and total walking distance. We discuss the tradeoff between processing time and solution quality through a parameter called A* speed. The tool is available for transit users on a day-to-day basis in Brazilian cities of up to 800,000 inhabitants and returns a variety of solutions within a couple of seconds.
引用
收藏
页码:557 / 578
页数:22
相关论文
共 50 条
  • [41] New Heuristic and Evolutionary Operators for the Multi-Objective Urban Transit Routing Problem
    Mumford, Christine L.
    2013 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2013, : 939 - 946
  • [42] Evaluating a Multi-Objective Hyper-Heuristic for the Integration and Test Order Problem
    Guizzo, Giovani
    Vergilio, Silvia R.
    Pozo, Aurora T. R.
    2015 BRAZILIAN CONFERENCE ON INTELLIGENT SYSTEMS (BRACIS 2015), 2015, : 1 - 6
  • [43] A Knowledge-Guided Multi-Objective Shuffled Frog Leaping Algorithm for Dynamic Multi-Depot Multi-Trip Vehicle Routing Problem
    Zhao, Yun
    Shen, Xiaoning
    Ge, Zhongpei
    SYMMETRY-BASEL, 2024, 16 (06):
  • [44] A New Multi-Layer Distributed Approach for a Multi-objective Planning Problem
    Mnif, Mouna
    Bouamama, Sadok
    KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS (KES 2019), 2019, 159 : 1406 - 1420
  • [45] Multi-Objective Trip Planning With Solution Ranking Based on User Preference and Restaurant Selection
    Choachaicharoenkul, Supoj
    Coit, David
    Wattanapongsakorn, Naruemon
    IEEE ACCESS, 2022, 10 : 10688 - 10705
  • [46] Collective Multi-Objective Planning
    Mouaddib, Abdel-Illah
    DIS 2006: IEEE WORKSHOP ON DISTRIBUTED INTELLIGENT SYSTEMS: COLLECTIVE INTELLIGENCE AND ITS APPLICATIONS, PROCEEDINGS, 2006, : 43 - 48
  • [47] Multi-objective Transmission Planning
    Xu, Zhao
    Dong, Zhao Yang
    Wong, Kit Po
    Fan, Zhun
    2009 ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC), VOLS 1-7, 2009, : 2082 - +
  • [48] Multi-Objective A* Algorithm for the Multimodal Multi-Objective Path Planning Optimization
    Jin, Bo
    2021 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC 2021), 2021, : 1704 - 1711
  • [49] The Development of Heuristic for Solving Multi Objective Mark Planning Problem in Garment Industry
    Puasakul, Kritsada
    Chaovalitwongse, Paveena
    2013 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT (IEEM 2013), 2013, : 743 - 747
  • [50] An efficient multi-objective meta-heuristic method for distribution network expansion planning
    Mori, Hiroyuki
    Yamada, Yoshinori
    2007 IEEE LAUSANNE POWERTECH, VOLS 1-5, 2007, : 374 - 379