A tabu search algorithm for a capacitated clustering problem
Sudha Khambhampati,
Prasad Calyam and
Xinhui Zhang
International Journal of Operational Research, 2018, vol. 33, issue 3, 387-412
Abstract:
This paper investigates a clustering problem in a production and routing environment where a centralised facility uses a fleet of vehicles to serve a set of customers. A multi-period capacitated clustering problem is solved to partition customer into clusters with constraints that the accumulated customer demand in every period of the planning horizon is satisfied. The resulting mathematical model is hard to solve exactly and efficient heuristics are thus developed in this paper. The heuristics are based on the tabu search but include two novel features in the design of neighbourhood search; the first one is the dynamic combination of customers with close proximity into supernodes to eliminate ineffective moves and the second one is an ejection chain approach to perform composite moves of variable length from a series of simple moves. Computational results showed that they were able to provide superior solutions, especially in certain cases of tight capacity constraints.
Keywords: capacitated clustering; heuristics; supernode; ejection chain; tabu search. (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.inderscience.com/link.php?id=95627 (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:ijores:v:33:y:2018:i:3:p:387-412
Access Statistics for this article
More articles in International Journal of Operational Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().