Skip to main content
Kent Academic Repository

A two-level evolutionary algorithm for solving the petrol station replenishment problem with periodicity constraints and service choice

Al-Hinai, Nasr, Triki, Chefi (2018) A two-level evolutionary algorithm for solving the petrol station replenishment problem with periodicity constraints and service choice. Annals of Operations Research, 286 (1-2). pp. 325-350. ISSN 0254-5330. E-ISSN 1572-9338. (doi:10.1007/s10479-018-3117-3) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:91497)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL:
http://dx.doi.org/10.1007/s10479-018-3117-3

Abstract

This paper addresses the petrol station replenishment problem with periodicity constraints and introduces the frequency service choice as a decision variable. We present a mathematical optimization model for the problem and we develop first a simple heuristic method that is able to handle the complexity of the problem and then two metaheuristic approaches based on a novel two-level evolutionary algorithm. The first level deals with the periodicity and frequency selection of the visits to the petrol stations. The second level of evolution assigns the stations to the tank-trucks such that the total traveled distance is minimized. The effectiveness of the proposed approaches has been tested by means of a comprehensive experimental study by using first a set of randomly generated test cases and then a real-life problem. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.

Item Type: Article
DOI/Identification number: 10.1007/s10479-018-3117-3
Uncontrolled keywords: Multi period planning, petrol station replenishment, tank trucks scheduling and routing, periodicity and frequency service choice
Subjects: H Social Sciences
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: Chefi Triki
Date Deposited: 18 Nov 2021 09:39 UTC
Last Modified: 19 Nov 2021 10:14 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/91497 (The current URI for this page, for reference purposes)

University of Kent Author Information

  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.