Solving the bi-objective optimisation problem with periodic delivery operations using a lexicographic method
Cheng-Hsiang Liu
International Journal of Production Research, 2016, vol. 54, issue 8, 2275-2283
Abstract:
Periodic deliveries are typical in a number of real-life applications. Minimising the number of vehicles required to make deliveries to a set of customers with known delivery frequencies is called the problem of vehicle minimisation for periodic deliveries (VMPD). Catering to the welfare of vehicle drivers has now become very important. Consequently, this work integrates the vehicle load balance factor into the VMPD problem by considering both the number of vehicles required to make periodic deliveries and the load balance between vehicles. This work presents integer programming formulations and applies a lexicographic method to this bi-objective VMPD problem. This work also examines whether decomposition can significantly reduce the size and difficulty of basic integer programming formulation in order to output close-to-optimal schedules for large problems within a reasonable computational time. A greedy balancing algorithm is also proposed to use it along with a decomposed integer programming formulation to yield a satisfactory solution in a relatively short time. Computational experiments demonstrate the better competitiveness of the proposed approaches compared to that of the existing approaches.
Date: 2016
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2015.1070969 (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:taf:tprsxx:v:54:y:2016:i:8:p:2275-2283
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20
DOI: 10.1080/00207543.2015.1070969
Access Statistics for this article
International Journal of Production Research is currently edited by Professor A. Dolgui
More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().