A comparison between optimization tools to solve sectorization problem

Aydin  Teymourifar; Ana Maria Rodrigues; José Soeiro  Ferreira; Cristina  Lopes

doi:10.1007/978-3-030-92666-3_4

A comparison between optimization tools to solve sectorization problem

Aydin Teymourifar^*
, Ana Maria Rodrigues
, José Soeiro Ferreira
, Cristina Lopes

^*Autor correspondente para este trabalho

Resultado de pesquisa › revisão de pares

4 Citações (Scopus)

383 Transferências (Pure)

Resumo

In sectorization problems, a large district is split into small ones, usually meeting certain criteria. In this study, at first, two single-objective integer programming models for sectorization are presented. Models contain sector centers and customers, which are known beforehand. Sectors are established by assigning a subset of customers to each center, regarding objective functions like equilibrium and compactness. Pulp and Pyomo libraries available in Python are utilised to solve related benchmarks. The problems are then solved using a genetic algorithm available in Pymoo, which is a library in Python that contains evolutionary algorithms. Furthermore, the multi-objective versions of the models are solved with NSGA-II and RNSGA-II from Pymoo. A comparison is made among solution approaches. Between solvers, Gurobi performs better, while in the case of setting proper parameters and operators the evolutionary algorithm in Pymoo is better in terms of solution time, particularly for larger benchmarks.

Idioma original	English
Título da publicação do anfitrião	Modelling, computation and optimization in information systems and management sciences
Subtítulo da publicação do anfitrião	proceedings of the 4th international conference on modelling, computation and optimization in information systems and management sciences - MCO 2021
Editores	Hoai An Le Thi, Hoai Minh Le, Hoai An Le Thi, Tao Pham Dinh
Editora	Springer
Páginas	40-50
Número de páginas	11
ISBN (impresso)	9783030926656
DOIs	https://doi.org/10.1007/978-3-030-92666-3_4
Estado da publicação	Publicado - 2022
Evento	4th International Conference on Modelling, Computation and Optimization in Information Systems and Management Sciences - Hanoi Duração: 13 dez. 2021 → 14 dez. 2021

Série de publicação

Nome	Lecture Notes in Networks and Systems
Volume	363 LNNS
ISSN (impresso)	2367-3370
ISSN (eletrónico)	2367-3389

Conferência

Conferência	4th International Conference on Modelling, Computation and Optimization in Information Systems and Management Sciences
Título abreviado	MCO 2021
País/Território	Viet Nam
Cidade	Hanoi
Período	13/12/21 → 14/12/21

Acesso ao documento

10.1007/978-3-030-92666-3_4

40015510Accepted author manuscript, 310 KBLicença: Unspecified

http://hdl.handle.net/10400.14/36554Licença: Unspecified

Outros arquivos e links

Link to publication in Scopus

Simulation and Analytical Techniques Applied to Management and Economics
Teymourifar, A. (PI)
Fundação para a Ciência e a Tecnologia
5/01/21 → 30/04/25
Projeto
CEGE: Research Center in Management and Economics
Silva, M. (Professor Catedrático), Sousa, R. (Professor Catedrático), Alves, P. (Professor Auxiliar), Madsen, A. (Professor Auxiliar Convidado), Lourenço, A. (Professor Associado), Carvalho, A. S. (Professor Associado), Andrade, A. (Professor Auxiliar), Silva, P. D. (Professor Associado), Vlačić, B. (Professor Auxiliar Convidado), Martins, C. (Professor Auxiliar Convidado), Gomes, C. (Investigador Auxiliar), Gevrek, Z. E. (Professor Auxiliar Convidado), Oliveira, F. G. D. (Professor Associado), Faria, G. (Professor Associado Convidado), Marreiros, H. (Bolseiro), Pinho, J. (Professor Auxiliar Convidado), Machado, J. (Professor Associado), Araújo, J. (Investigador Auxiliar), Pinto, J. (Professor Auxiliar), Rego, A. (Professor Catedrático), Gaspar, J. M. (Investigador Auxiliar), Corbo, L. (Professor Auxiliar Convidado), Costa, L. (Professor Associado), Fernandes, L. (Professor Auxiliar), Sottomayor, M. (Professor Auxiliar), Martins, N. (Professor Catedrático), Hernández-Marrero, P. (Investigador Auxiliar), Gonçalves, R. (Professor Associado), Ribeiro, R. (PI), Coelho, S. L. (Docente Assistente), Pereira, S. M. (Investigador Auxiliar), Silva, S. (Professor Associado), Rodrigues, V. (Professor Associado), Sotiros, D. G. (Investigador Auxiliar), Valverde, C. (Professor Auxiliar), Leitão, A. (Professor Auxiliar), Julião, J. (Professor Auxiliar), Tavares, M. (Professor Auxiliar), Lages, C. R. (Investigador Auxiliar), Elmashhara, M. G. (Investigador Auxiliar) & Teymourifar, A. (Investigador Auxiliar)
1/01/20 → 31/12/25
Projeto

Citação

Teymourifar, A., Rodrigues, A. M., Ferreira, J. S., & Lopes, C. (2022). A comparison between optimization tools to solve sectorization problem. Em H. A. Le Thi, H. M. Le, H. A. Le Thi, & T. Pham Dinh (Eds.), Modelling, computation and optimization in information systems and management sciences: proceedings of the 4th international conference on modelling, computation and optimization in information systems and management sciences - MCO 2021 (pp. 40-50). (Lecture Notes in Networks and Systems; Vol. 363 LNNS). Springer. https://doi.org/10.1007/978-3-030-92666-3_4

Teymourifar, Aydin ; Rodrigues, Ana Maria ; Ferreira, José Soeiro et al. / A comparison between optimization tools to solve sectorization problem. Modelling, computation and optimization in information systems and management sciences: proceedings of the 4th international conference on modelling, computation and optimization in information systems and management sciences - MCO 2021. editor / Hoai An Le Thi ; Hoai Minh Le ; Hoai An Le Thi ; Tao Pham Dinh. Springer, 2022. pp. 40-50 (Lecture Notes in Networks and Systems).

@inproceedings{781f436bff7d4bd2b38aafab8b643969,

title = "A comparison between optimization tools to solve sectorization problem",

abstract = "In sectorization problems, a large district is split into small ones, usually meeting certain criteria. In this study, at first, two single-objective integer programming models for sectorization are presented. Models contain sector centers and customers, which are known beforehand. Sectors are established by assigning a subset of customers to each center, regarding objective functions like equilibrium and compactness. Pulp and Pyomo libraries available in Python are utilised to solve related benchmarks. The problems are then solved using a genetic algorithm available in Pymoo, which is a library in Python that contains evolutionary algorithms. Furthermore, the multi-objective versions of the models are solved with NSGA-II and RNSGA-II from Pymoo. A comparison is made among solution approaches. Between solvers, Gurobi performs better, while in the case of setting proper parameters and operators the evolutionary algorithm in Pymoo is better in terms of solution time, particularly for larger benchmarks.",

keywords = "Gurobi, Optimization, Pulp, Pymoo, Pyomo, Sectorization",

author = "Aydin Teymourifar and Rodrigues, \{Ana Maria\} and Ferreira, \{Jos{\'e} Soeiro\} and Cristina Lopes",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 4th International Conference on Modelling, Computation and Optimization in Information Systems and Management Sciences, MCO 2021 ; Conference date: 13-12-2021 Through 14-12-2021",

year = "2022",

doi = "10.1007/978-3-030-92666-3\_4",

language = "English",

isbn = "9783030926656",

series = "Lecture Notes in Networks and Systems",

publisher = "Springer",

pages = "40--50",

editor = "\{Le Thi\}, \{Hoai An\} and Le, \{Hoai Minh\} and \{Le Thi\}, \{Hoai An\} and \{Pham Dinh\}, Tao",

booktitle = "Modelling, computation and optimization in information systems and management sciences",

address = "Germany",

}

Teymourifar, A, Rodrigues, AM, Ferreira, JS & Lopes, C 2022, A comparison between optimization tools to solve sectorization problem. em HA Le Thi, HM Le, HA Le Thi & T Pham Dinh (eds), Modelling, computation and optimization in information systems and management sciences: proceedings of the 4th international conference on modelling, computation and optimization in information systems and management sciences - MCO 2021. Lecture Notes in Networks and Systems, vol. 363 LNNS, Springer, pp. 40-50, 4th International Conference on Modelling, Computation and Optimization in Information Systems and Management Sciences, Hanoi, Viet Nam, 13/12/21. https://doi.org/10.1007/978-3-030-92666-3_4

A comparison between optimization tools to solve sectorization problem. / Teymourifar, Aydin ; Rodrigues, Ana Maria; Ferreira, José Soeiro et al.
Modelling, computation and optimization in information systems and management sciences: proceedings of the 4th international conference on modelling, computation and optimization in information systems and management sciences - MCO 2021. ed. / Hoai An Le Thi; Hoai Minh Le; Hoai An Le Thi; Tao Pham Dinh. Springer, 2022. p. 40-50 (Lecture Notes in Networks and Systems; Vol. 363 LNNS).

Resultado de pesquisa › revisão de pares

TY - GEN

T1 - A comparison between optimization tools to solve sectorization problem

AU - Teymourifar, Aydin

AU - Rodrigues, Ana Maria

AU - Ferreira, José Soeiro

AU - Lopes, Cristina

PY - 2022

Y1 - 2022

N2 - In sectorization problems, a large district is split into small ones, usually meeting certain criteria. In this study, at first, two single-objective integer programming models for sectorization are presented. Models contain sector centers and customers, which are known beforehand. Sectors are established by assigning a subset of customers to each center, regarding objective functions like equilibrium and compactness. Pulp and Pyomo libraries available in Python are utilised to solve related benchmarks. The problems are then solved using a genetic algorithm available in Pymoo, which is a library in Python that contains evolutionary algorithms. Furthermore, the multi-objective versions of the models are solved with NSGA-II and RNSGA-II from Pymoo. A comparison is made among solution approaches. Between solvers, Gurobi performs better, while in the case of setting proper parameters and operators the evolutionary algorithm in Pymoo is better in terms of solution time, particularly for larger benchmarks.

AB - In sectorization problems, a large district is split into small ones, usually meeting certain criteria. In this study, at first, two single-objective integer programming models for sectorization are presented. Models contain sector centers and customers, which are known beforehand. Sectors are established by assigning a subset of customers to each center, regarding objective functions like equilibrium and compactness. Pulp and Pyomo libraries available in Python are utilised to solve related benchmarks. The problems are then solved using a genetic algorithm available in Pymoo, which is a library in Python that contains evolutionary algorithms. Furthermore, the multi-objective versions of the models are solved with NSGA-II and RNSGA-II from Pymoo. A comparison is made among solution approaches. Between solvers, Gurobi performs better, while in the case of setting proper parameters and operators the evolutionary algorithm in Pymoo is better in terms of solution time, particularly for larger benchmarks.

KW - Gurobi

KW - Optimization

KW - Pulp

KW - Pymoo

KW - Pyomo

KW - Sectorization

UR - https://www.scopus.com/pages/publications/85121898105

U2 - 10.1007/978-3-030-92666-3_4

DO - 10.1007/978-3-030-92666-3_4

M3 - Conference contribution

SN - 9783030926656

T3 - Lecture Notes in Networks and Systems

SP - 40

EP - 50

BT - Modelling, computation and optimization in information systems and management sciences

A2 - Le Thi, Hoai An

A2 - Le, Hoai Minh

A2 - Le Thi, Hoai An

A2 - Pham Dinh, Tao

PB - Springer

T2 - 4th International Conference on Modelling, Computation and Optimization in Information Systems and Management Sciences

Y2 - 13 December 2021 through 14 December 2021

ER -

Teymourifar A, Rodrigues AM, Ferreira JS, Lopes C. A comparison between optimization tools to solve sectorization problem. Em Le Thi HA, Le HM, Le Thi HA, Pham Dinh T, editores, Modelling, computation and optimization in information systems and management sciences: proceedings of the 4th international conference on modelling, computation and optimization in information systems and management sciences - MCO 2021. Springer. 2022. p. 40-50. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-030-92666-3_4

A comparison between optimization tools to solve sectorization problem

Resumo

Série de publicação

Conferência

Acesso ao documento

Outros arquivos e links

Impressão digital

Projetos

Simulation and Analytical Techniques Applied to Management and Economics

CEGE: Research Center in Management and Economics

Citação