Maximal covering salesman problems with average travelling cost constrains

Mostafa Dastmardi, Mohammad Mohammadi and Bahman Naderi

International Journal of Mathematics in Operational Research, 2020, vol. 17, issue 2, 153-169

Abstract: We study the maximal covering salesman problem with the average travelling cost constraints (MCSPATCC) where the objective is to find a subset of customers with their tour so that the number of covered demand points is maximised. This paper presents a mathematical model to select a profitable subset of demand points to be covered. We also propose an effective heuristic algorithm with three elimination methods to remove unprofitable demand points. The proposed algorithm is based on the genetic algorithm (GA) hybridised with different local search strategies to solve this problem. Parameters of the algorithm are analysed for calibration by the Taguchi method. Extensive computational experiments, on a set of standard problems, have indicated the effectiveness of our algorithm.

Keywords: maximum covering; genetic algorithm; covering salesman problem. (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=109693 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijmore:v:17:y:2020:i:2:p:153-169

Access Statistics for this article

More articles in International Journal of Mathematics in Operational Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().