Solving the interval green inventory routing problem using optimization and genetic algorithms

Carlos Franco, Eduyn Ramiro López-Santana, Juan Carlos Figueroa-García

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

In this paper, we present a genetic algorithm embedded with mathematical optimization to solve a green inventory routing problem with interval fuel consumption. Using the idea of column generation in which only attractive routes are generated to the mathematical problem, we develop a genetic algorithm that allow us to determine speedily attractive routes that are connected to a mathematical model. We code our genetic algorithm using the idea of a integer number that represents all the feasible set of routes in which the maximum number allowed is the binary number that represents if a customer is visited or not. We approximate the fuel consumption as an interval number in which we want to minimize the overall fuel consumption of distribution. This is the first approximation made in the literature using this type of methodology so we cannot compare our approach with those used in the literature.

Original languageEnglish (US)
Title of host publicationApplied Computer Sciences in Engineering - 4th Workshop on Engineering Applications, WEA 2017, Proceedings
EditorsJuan Carlos Figueroa-Garcia, Eduyn Ramiro Lopez-Santana, Roberto Ferro-Escobar, Jose Luis Villa-Ramirez
PublisherSpringer
Pages556-564
Number of pages9
ISBN (Print)9783319669625
DOIs
StatePublished - 2017
Event4th Workshop on Engineering Applications, WEA 2017 - Cartagena, Colombia
Duration: Sep 27 2017Sep 29 2017

Publication series

NameCommunications in Computer and Information Science
Volume742
ISSN (Print)1865-0929

Conference

Conference4th Workshop on Engineering Applications, WEA 2017
CountryColombia
CityCartagena
Period9/27/179/29/17

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Mathematics(all)

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