An Integer Programming Approach to Sectorization with Compactness and Equilibrium Constraints

Romanciuc, Valeria; Lopes, Cristina Videira; Teymourifar, Aydin; Rodrigues, Ana Maria; Ferreira, José Soeiro; Oliveira, Cristina; Öztürk, Elif Göksu

doi:10.1007/978-3-030-78170-5_17

Cited by 2 publications

(4 citation statements)

References 13 publications

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“…Parameters τ ranges inside the interval [0, 1]. Two-dimensional coordinates of clients and center of sectors and likewise clients' demands, are created according to N (50;10) and U (10;100), which are normal and discrete uniform distributions, respectively [13] , [14] , [17] , [18] .…”

Section: Resultsmentioning

confidence: 99%

“…In this study, a comparison is made between optimization software to solve a sectorization problem (SP). The goal of SPs is to split a large region into smaller ones for administrative purposes [11] , [12] , [13] , [14] . However the main contribution of the study to the literature is the comparison among optimization software, it has other novelties, which can be summarized as follows: A new bi-objective (BO) model is defined for SP, which is nonlinear (NL).…”

Section: Introductionmentioning

confidence: 99%

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A comparison among optimization software to solve bi-objective sectorization problem

Teymourifar¹

2023

Heliyon

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A comparison among optimization software to solve bi-objective sectorization problem

Teymourifar¹

2023

Heliyon

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“…In this model, as defined in Equation 2, compactness is the objective function, while equilibrium is satisfied with a constraint. Compactness is defined based on measuring the total distance of the points to the center of the assigned sector [19,20].…”

Section: Sc: So Model To Minimize Compactnessmentioning

confidence: 99%

“…In this model, the objective function as defined in Equation 9, considers both compactness and equilibrium, based on the Pareto optimality concept [20].…”

Section: Mce: Mo Model To Minimize Compactness and To Maximize Equili...mentioning

confidence: 99%

A Comparison Between Optimization Tools to Solve Sectorization Problem

Teymourifar

Rodrigues

Ferreira

et al. 2021

Modelling, Computation and Optimization in Information Systems and Management Sciences

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In sectorization problems, a large district is split into small ones, usually meeting certain criteria. In this study, at first, two singleobjective 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.

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An Integer Programming Approach to Sectorization with Compactness and Equilibrium Constraints

Cited by 2 publications

References 13 publications

A comparison among optimization software to solve bi-objective sectorization problem

A comparison among optimization software to solve bi-objective sectorization problem

A Comparison Between Optimization Tools to Solve Sectorization Problem

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