TY - CHAP
T1 - A comparison between simultaneous and hierarchical approaches to solve a multi-objective location-routing problem
AU - Teymourifar, Aydin
AU - Rodrigues, Ana Maria
AU - Ferreira, José Soeiro
N1 - Funding Information:
Acknowledgments This work is financed by the ERDF—European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation—COMPETE 2020 Programme and by National Funds through the Portuguese funding agency, FCT—Fundao para a Ciłncia e a Tecnologia within project POCI-01-0145-FEDER-031671.
Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.
PY - 2021
Y1 - 2021
N2 - This paper deals with a multi-objective location-routing problem (MO-LRP) and follows the idea of sectorization to simplify the solution approaches. The MO-LRP consists of sectorization, sub-sectorization, and routing sub-problems. In the sectorization sub-problem, a subset of potential distribution centres (DCs) is opened and a subset of customers is assigned to each of them. Each DC and the customers assigned to it form a sector. Afterward, in the sub-sectorization stage customers of each DC are divided into different sub-sector. Then, in the routing sub-problem, a route is determined and a vehicle is assigned to meet demands. To solve the problem, we design two approaches, which adapt the sectorization, sub-sectorization and routing sub-problems with the non-dominated sorting genetic algorithm (NSGA-II) in two different manners. In the first approach, NSGA-II is used to find non-dominated solutions for all sub-problems, simultaneously. The second one is similar to the first one but it has a hierarchical structure, such that the routing sub-problem is solved with a solver for binary integer programming in MATLAB optimization toolbox after solving sectorization and sub-sectorization sub-problem with NSGA-II. Four benchmarks are used and based on a comparison between the obtained results it is shown that the first approach finds more non-dominated solutions. Therefore, it is concluded that the simultaneous approach is more effective than the hierarchical approach for the defined problem in terms of finding more non-dominated solutions.
AB - This paper deals with a multi-objective location-routing problem (MO-LRP) and follows the idea of sectorization to simplify the solution approaches. The MO-LRP consists of sectorization, sub-sectorization, and routing sub-problems. In the sectorization sub-problem, a subset of potential distribution centres (DCs) is opened and a subset of customers is assigned to each of them. Each DC and the customers assigned to it form a sector. Afterward, in the sub-sectorization stage customers of each DC are divided into different sub-sector. Then, in the routing sub-problem, a route is determined and a vehicle is assigned to meet demands. To solve the problem, we design two approaches, which adapt the sectorization, sub-sectorization and routing sub-problems with the non-dominated sorting genetic algorithm (NSGA-II) in two different manners. In the first approach, NSGA-II is used to find non-dominated solutions for all sub-problems, simultaneously. The second one is similar to the first one but it has a hierarchical structure, such that the routing sub-problem is solved with a solver for binary integer programming in MATLAB optimization toolbox after solving sectorization and sub-sectorization sub-problem with NSGA-II. Four benchmarks are used and based on a comparison between the obtained results it is shown that the first approach finds more non-dominated solutions. Therefore, it is concluded that the simultaneous approach is more effective than the hierarchical approach for the defined problem in terms of finding more non-dominated solutions.
KW - Binary integer programming
KW - Evolutionary algorithm
KW - Location-routing problems
KW - Non-dominated sorting genetic algorithm
KW - Routing
KW - Sectorization
UR - http://www.scopus.com/inward/record.url?scp=85107081381&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-63072-0_20
DO - 10.1007/978-3-030-63072-0_20
M3 - Chapter
AN - SCOPUS:85107081381
SN - 9783030630720
T3 - AIRO Springer Series
SP - 251
EP - 263
BT - AIRO Springer Series
A2 - Gentile, Claudio
A2 - Stecca, Giuseppe
A2 - Ventura, Paolo
PB - Springer Nature
ER -