Dynamic virtual bats algorithm (DVBA) for minimization of supply chain cost with embedded risk

Ali Osman Topal, Oguz Altun, Erisa Terolli

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Dynamic Virtual Bats Algorithm (DVBA) is a new optimization algorithm, which is tested on several benchmark functions for global optimization. However it has not been tested on a real world problem yet. In this paper DVBA has been applied to minimize the supply chain cost with other well known algorithms, Particle Swarm Optimization (PSO), Bat Algorithm (BA), Genetic Algorithm (GA) and Tabu Search (TS). Optimization of supply chain is considered as a real challenge by researchers because of its complexity. Big number of parameters to be controlled and their distributions, interconnections between parameters and dynamism are the main factors that increase the complexity of a supply chain. The result of the case study showed that the DVBA is much superior to other algorithms in terms of accuracy and efficiency.

Original languageEnglish
Title of host publicationProceedings - UKSim-AMSS 8th European Modelling Symposium on Computer Modelling and Simulation, EMS 2014
EditorsDavid Al-Dabass, Marco Vannucci, Athanasios Pantelous, Valentina Colla
Pages58-64
Number of pages7
ISBN (Electronic)9781479974115
DOIs
StatePublished - 2014
EventUKSim-AMSS 8th European Modelling Symposium on Computer Modelling and Simulation, EMS 2014 - Pisa, Italy
Duration: 21 Oct 201423 Oct 2014

Publication series

NameProceedings - UKSim-AMSS 8th European Modelling Symposium on Computer Modelling and Simulation, EMS 2014

Conference

ConferenceUKSim-AMSS 8th European Modelling Symposium on Computer Modelling and Simulation, EMS 2014
Country/TerritoryItaly
CityPisa
Period21/10/1423/10/14

Keywords

  • Computational intelligence techniques
  • Dynamic Virtual Bats Algorithm (DVBA)
  • Supply Chain Cost Problem

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