78
Views
8
CrossRef citations to date
0
Altmetric
Original Article

A comparative study of heuristic algorithms for the multiple target access problem

&
Pages 437-449 | Received 23 Aug 2013, Accepted 21 Nov 2013, Published online: 03 Jan 2014
 

Abstract

Through computational experiments, we conducted a comparative study of the performance of heuristic algorithms for the multiple target access problem (MTAP). MTAP requires the minimum cost road network accessible to given targets on forest land to be designed via the construction of new roads from existing road networks. We first show that MTAP can be transformed into the Steiner tree problem (STP) in graph theory, by identifying nodes representing existing road networks. This allows us to use STP algorithms for solving MTAP. Because of NP-hardness of STP, we apply heuristic algorithms in this study. In our computational experiments, each of 14 heuristic STP algorithms, of which many have the performance guarantee of twice the optimal, solves 1,120 MTAP instances with various properties. Upon analysis of the results, we conclude that the average distance heuristic (ADH) and repetitive applications of the shortest path heuristic (SPH-V, SPH- Z, SPH-zZ, and SPH-ZZ) exhibit consistently superior performance in terms of solution quality. Additionally, we confirm that ADH, SPH-V, and SPH-ZZ design similarly shaped road network layouts.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 159.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.