A Multi Ant Colony Optimization algorithm for a Mixed Car Assembly Line

Pulido Martínez, Raúl, García Sánchez, Álvaro ORCID: https://orcid.org/0000-0001-5774-1430, Diego, Francisco Javier and Andrés-Romano, Carlos (2013). A Multi Ant Colony Optimization algorithm for a Mixed Car Assembly Line. In: "IX Congreso Español de Metaheurísticas, Algoritmos Evolutivos y Bioinspirados - MAEB 2013", 17/09/2013 - 20/09/2013, Madrid. ISBN 978-84-695-8348-7. pp. 424-432.

Description

Title: A Multi Ant Colony Optimization algorithm for a Mixed Car Assembly Line
Author/s:
  • Pulido Martínez, Raúl
  • García Sánchez, Álvaro https://orcid.org/0000-0001-5774-1430
  • Diego, Francisco Javier
  • Andrés-Romano, Carlos
Item Type: Presentation at Congress or Conference (Article)
Event Title: IX Congreso Español de Metaheurísticas, Algoritmos Evolutivos y Bioinspirados - MAEB 2013
Event Dates: 17/09/2013 - 20/09/2013
Event Location: Madrid
Title of Book: XV Multiconferencia CAEPIA
Date: 2013
ISBN: 978-84-695-8348-7
Subjects:
Freetext Keywords: Ant Colony Optimization, Vehicle Routing Problem, Car Sequencing
Faculty: E.T.S.I. Industriales (UPM)
Department: Ingeniería de Organización, Administración de Empresas y Estadística
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

This paper presents an ant colony optimization algorithm to sequence the mixed assembly lines considering the inventory and the replenishment of components. This is a NP-problem that cannot be solved to optimality by exact methods when the size of the problem growth. Groups of specialized ants are implemented to solve the different parts of the problem. This is intended to differentiate each part of the problem. Different types of pheromone structures are created to identify good car sequences, and good routes for the replenishment of components vehicle. The contribution of this paper is the collaborative approach of the ACO for the mixed assembly line and the replenishment of components and the jointly solution of the problem.

More information

Item ID: 33289
DC Identifier: https://oa.upm.es/33289/
OAI Identifier: oai:oa.upm.es:33289
Official URL: http://bioinspired.dacya.ucm.es/maeb2013/
Deposited by: Memoria Investigacion
Deposited on: 18 Feb 2015 16:47
Last Modified: 21 Mar 2017 16:03
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