RoutingBlocks: An Open-Source Python']Python Package for Vehicle Routing Problems with Intermediate Stops

被引:2
|
作者
Klein, Patrick S. [1 ]
Schiffer, Maximilian [1 ,2 ]
机构
[1] Tech Univ Munich, TUM Sch Management, D-80333 Munich, Germany
[2] Tech Univ Munich, Munich Data Sci Inst, D-80333 Munich, Germany
关键词
vehicle routing; metaheuristic algorithms; !text type='Python']Python[!/text; open-source software; SOLUTION FRAMEWORK;
D O I
10.1287/ijoc.2023.0104
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
We introduce RoutingBlocks, a versatile open-source Python package designed to simplify the development of algorithms for vehicle routing problems with intermediate stops (VRPIS). The package offers a variety of modular algorithmic components and optimized data structures crafted specifically to address key challenges of VRPIS, such as a lack of exact constant-time move evaluations and difficult station visit decisions. By using a unified solution and instance representation that abstracts problemspecific behavior, for example, constraint checking, move evaluation, and cost computation, into well-defined interfaces, RoutingBlocks maintains a clear separation between algorithmic components and specific problem configurations, thus allowing the application of the same algorithm to a variety of problem settings. Leveraging an efficient C++ implementation for performance-critical core elements, RoutingBlocks combines the high performance of C++ with the user-friendliness and adaptability of Python, thereby streamlining the development of effective metaheuristic algorithms. As a result, researchers using RoutingBlocks can focus on their algorithms' core features, allocating more resources to innovation and advancement in the VRPIS domain.
引用
收藏
页码:966 / 973
页数:8
相关论文
共 50 条
  • [31] StormReactor: An open-source Python']Python package for the integrated modeling of urban water quality and water balance
    Mason, Brooke E.
    Mullapudi, Abhiram
    Kerkez, Branko
    ENVIRONMENTAL MODELLING & SOFTWARE, 2021, 145
  • [32] mfapy: An open-source Python']Python package for 13C-based metabolic flux analysis
    Matsuda, Fumio
    Maeda, Kousuke
    Taniguchi, Takeo
    Kondo, Yuya
    Yatabe, Futa
    Okahashi, Nobuyuki
    Shimizu, Hiroshi
    METABOLIC ENGINEERING COMMUNICATIONS, 2021, 13
  • [33] QmeQ 1.0: An open-source Python']Python package for calculations of transport through quantum dot devices
    Kirsanskas, Gediminas
    Pedersen, Jonas Nyvold
    Karlstrom, Olov
    Leijnse, Martin
    Wacker, Andreas
    COMPUTER PHYSICS COMMUNICATIONS, 2017, 221 : 317 - 342
  • [34] Precision-medicine-toolbox: An open-source python']python package for the quantitative medical image analysis
    Lavrova, Elizaveta
    Primakov, Sergey
    Salahuddin, Zohaib
    Beuque, Manon
    Verstappen, Damon
    Woodruff, Henry C.
    Lambin, Philippe
    SOFTWARE IMPACTS, 2023, 16
  • [35] Pyomo.DOE: An open-source package for model-based design of experiments in Python']Python
    Wang, Jialu
    Dowling, Alexander W.
    AICHE JOURNAL, 2022, 68 (12)
  • [36] PAMI: An Open-Source Python']Python Library for Pattern Mining
    Kiran, R. Uday
    Veena, P.
    Toyoda, Masashi
    Kitsuregawa, Masaru
    JOURNAL OF MACHINE LEARNING RESEARCH, 2024, 25 : 1 - 6
  • [37] OSAFT Library: An Open-Source Python']Python Library for Acoustofluidics
    Fankhauser, Jonas
    Goering, Christoph
    Dual, Juerg
    FRONTIERS IN PHYSICS, 2022, 10
  • [38] Padasip: An open-source Python']Python toolbox for adaptive filtering
    Cejnek, Matous
    Vrba, Jan
    JOURNAL OF COMPUTATIONAL SCIENCE, 2022, 65
  • [39] Open-source coupled aerostructural optimization using Python']Python
    Jasa, John P.
    Hwang, John T.
    Martins, Joaquim R. R. A.
    STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2018, 57 (04) : 1815 - 1827
  • [40] Python']Python Materials Genomics (pymatgen): A robust, open-source python']python library for materials analysis
    Ong, Shyue Ping
    Richards, William Davidson
    Jain, Anubhav
    Hautier, Geoffroy
    Kocher, Michael
    Cholia, Shreyas
    Gunter, Dan
    Chevrier, Vincent L.
    Persson, Kristin A.
    Ceder, Gerbrand
    COMPUTATIONAL MATERIALS SCIENCE, 2013, 68 : 314 - 319