TY - GEN

T1 - Solving the interval green inventory routing problem using optimization and genetic algorithms

AU - Franco, Carlos

AU - López-Santana, Eduyn Ramiro

AU - Figueroa-García, Juan Carlos

N1 - Publisher Copyright:
© 2017, Springer International Publishing AG.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.

PY - 2017

Y1 - 2017

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85030033946&partnerID=8YFLogxK

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U2 - 10.1007/978-3-319-66963-2_49

DO - 10.1007/978-3-319-66963-2_49

M3 - Conference contribution

AN - SCOPUS:85030033946

SN - 9783319669625

T3 - Communications in Computer and Information Science

SP - 556

EP - 564

BT - Applied Computer Sciences in Engineering - 4th Workshop on Engineering Applications, WEA 2017, Proceedings

A2 - Figueroa-Garcia, Juan Carlos

A2 - Lopez-Santana, Eduyn Ramiro

A2 - Ferro-Escobar, Roberto

A2 - Villa-Ramirez, Jose Luis

PB - Springer

T2 - 4th Workshop on Engineering Applications, WEA 2017

Y2 - 27 September 2017 through 29 September 2017

ER -