Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Help & Advice
University of Warwick

The Library

  • Login
  • Admin

Finding all Pareto optimal paths by simulating ripple relay race in multi-objective networks

Tools
- Tools
+ Tools

Hu, Xiao-Bing, Gu, Sheng-Hao, Zhang, Chi, Zhang, Gong-Peng, Zhang, Ming-Kong and Leeson, Mark S. (2021) Finding all Pareto optimal paths by simulating ripple relay race in multi-objective networks. Swarm and Evolutionary Computation, 64 . 100908. doi:10.1016/j.swevo.2021.100908

[img]
Preview
PDF
WRAP-Finding-Pareto-optimal-simulating-ripple-relay-race-multi-objective-networks-2021.pdf - Accepted Version - Requires a PDF viewer.
Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0.

Download (1451Kb) | Preview
Official URL: http://dx.doi.org/10.1016/j.swevo.2021.100908

Request Changes to record.

Abstract

This paper proposes a novel nature-inspired method, so-called ripple-spreading algorithm (RSA) for multi-objective path optimization problem (MOPOP). Unlike most existing methods mainly capable of finding partial or approximated Pareto front, this paper focuses on calculating the complete Pareto front. This is achieved by taking advantage of the optimality principle in natural ripple-spreading phenomenon. Basically, the proposed RSA carries out a one-off ripple relay race in the route network, and then the complete Pareto front will be identified with guaranteed optimality by backtracking those Pareto non-dominated ripples (PNDRs) which reached the destination node. Theoretical analyses and comprehensive experiments show that all complete Pareto fronts of a one-to-all MOPOP can also be found in just a single run of ripple relay race, and the reported method can be further extended to calculate all Pareto optimal paths in dynamical networks, which have rarely been touched by existing MOPOP methods. Since many real-world application problems can be converted into MOPOP, the reported method has a great potential of applications.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Science, Engineering and Medicine > Engineering > Engineering
Library of Congress Subject Headings (LCSH): Mathematical optimization , Evolutionary computation, Computer algorithms, Path analysis (Statistics) -- Computer programs
Journal or Publication Title: Swarm and Evolutionary Computation
Publisher: Elsevier BV
ISSN: 2210-6502
Official Date: July 2021
Dates:
DateEvent
July 2021Published
24 May 2021Available
12 May 2021Accepted
Volume: 64
Article Number: 100908
DOI: 10.1016/j.swevo.2021.100908
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
61472041[NSFC] National Natural Science Foundation of Chinahttp://dx.doi.org/10.13039/501100001809

Request changes or add full text files to a record

Repository staff actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics

twitter

Email us: wrap@warwick.ac.uk
Contact Details
About Us