An Extendable Platform for Routing Problem: Optimisation, Evaluation and Solution Visualisation

Chenhao LI, Jiyuan PEI, Qingquan ZHANG, Jialin LIU, Xin YAO

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review


A variety of routing problems have been formalised based on the applications in real life and their specific constraints. Diverse solvers based on one or more exact or approximate algorithms have been designed separately for optimising such problems. In most of the existing works, only the quality of the best solution found within a certain computational time is reported, while its corresponding solution is omitted. However, when the difference between the solution quality is small, decision-makers are more interested in how the actual solutions are and their diversity in decision space. In this paper, we design and implement an online platform that (i) is webpage based, with a uniform online computation environment; (ii) includes a number of routing problem models, problem instances, and solvers; (iii) includes a list of evaluation metrics and allows the visualisation of solutions in different ways for an easier comparison between solvers or solutions; (iv) is extendable, thus, offers the functionality of adding new problems, instances, solvers and evaluation metrics. We also present a novel fast cluster-based genetic algorithm for large-scale travelling salesman problems and perform a study using the proposed platform. © 2020 IEEE.
Original languageEnglish
Title of host publication2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages8
ISBN (Print)9781728125473
Publication statusPublished - 1 Dec 2020
Externally publishedYes


  • capacitated arc routing problem
  • meta-heuristics
  • Routing problem
  • travelling salesman problem


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