Modified artificial bee colony for the vehicle routing problems with time windows

Malek Alzaqebah, Salwani Abdullah, Sana Jawarneh

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

The natural behaviour of the honeybee has attracted the attention of researchers in recent years and several algorithms have been developed that mimic swarm behaviour to solve optimisation problems. This paper introduces an artificial bee colony (ABC) algorithm for the vehicle routing problem with time windows (VRPTW). A Modified ABC algorithm is proposed to improve the solution quality of the original ABC. The high exploration ability of the ABC slows-down its convergence speed, which may due to the mechanism used by scout bees in replacing abandoned (unimproved) solutions with new ones. In the Modified ABC a list of abandoned solutions is used by the scout bees to memorise the abandoned solutions, then the scout bees select a solution from the list based on roulette wheel selection and replace by a new solution with random routs selected from the best solution. The performance of the Modified ABC is evaluated on Solomon benchmark datasets and compared with the original ABC. The computational results demonstrate that the Modified ABC outperforms the original ABC also produce good solutions when compared with the best-known results in the literature. Computational investigations show that the proposed algorithm is a good and promising approach for the VRPTW.

Original languageEnglish
Article number1298
JournalSpringerPlus
Volume5
Issue number1
DOIs
Publication statusPublished - 1 Dec 2016

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Vehicle routing
Wheels

Keywords

  • Artificial bee colony
  • Foraging behaviour
  • Vehicle routing problem with time windows

ASJC Scopus subject areas

  • General

Cite this

Modified artificial bee colony for the vehicle routing problems with time windows. / Alzaqebah, Malek; Abdullah, Salwani; Jawarneh, Sana.

In: SpringerPlus, Vol. 5, No. 1, 1298, 01.12.2016.

Research output: Contribution to journalArticle

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