Multiobjective Genetic Algorithms for Reinforcing Equal Population in Congressional Districts

Lara-Caballero, Alejandro; Silva, Sergio Gerardo de los Cobos; Mora-Gutiérrez, Roman Anselmo; García, Eric Alfredo Rincón; Andrade, Miguel Ángel Gutiérrez; Lara-Velázquez, Pedro

doi:10.1155/2019/2825854

Cited by 4 publications

(2 citation statements)

References 35 publications

(54 reference statements)

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“…For an introduction to multiobjective genetic algorithms, one can refer to the relevant literature, such as the literature [44][45][46]. In general, genetic algorithms are search heuristic that is inspired by Charles Darwin's theory of natural evolution; the algorithm is an idea for solving the problem.…”

Section: Algorithm Designmentioning

confidence: 99%

Research on the Coordination Model of Passenger Transportation Mode in the Intercity Comprehensive Transportation Corridor

Liao

2022

Mathematical Problems in Engineering

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At present, the study of comprehensive transportation corridors primarily focuses on the planning and construction of transportation corridors. There are few studies on the coordinated operation of all modes of transportation after the construction of the transportation corridor is completed. Comprehensive transportation corridor takes on the characteristics that the volume of transport demand and supply is large, the number of transportation modes is not only one, and competition among different transportation modes is fierce. In order to prevent unhealthy competition among different transportation modes from disrupting the transportation market, this paper takes the passenger transportation modes within the intercity comprehensive transportation corridor as the studied object and establishes a coordination model for them. The model introduces the disaggregate model as the research theory, takes the quantizable attributes of transportation modes as the decision variables, takes the reasonable distribution of passenger flow among different transportation modes as the objective function, and takes the supply capacity of different transportation modes and the reasonable value range of decision variables as the constraints. This model is a multiobjective nonlinear programming problem. The multiobjective genetic algorithm is designed to solve the model. The real number encoding method is adopted to encode the decision variables; the penalty function method is used to eliminate the solutions that do not meet the nonlinear constraints after crossover and mutation; the repairment algorithm is used to convert the solutions that do not satisfy the linear constraints and bound constraints after crossover and mutation into the feasible region. Pareto optimal solution set is obtained through continuous selection, crossover, and mutation. Finally, a numeric example is made to demonstrate that the method proposed in this paper is effective and feasible.

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Section: Algorithm Designmentioning

confidence: 99%

Research on the Coordination Model of Passenger Transportation Mode in the Intercity Comprehensive Transportation Corridor

Liao

2022

Mathematical Problems in Engineering

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“…For MPGAs, mutation can be a supplementary strategy to maintain diversity [35]. Based on the characteristic of integer encoding, it is divided into two stages.…”

Section: Mutationmentioning

confidence: 99%

Multipopulation Genetic Algorithms with Different Interaction Structures to Solve Flexible Job-Shop Scheduling Problems: A Network Science Perspective

Deng

Long

et al. 2020

Mathematical Problems in Engineering

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Populations of multipopulation genetic algorithms (MPGAs) parallely evolve with some interaction mechanisms. Previous studies have shown that the interaction structures can impact on the performance of MPGAs to some extent. This paper introduces the concept of complex networks such as ring-shaped networks and small-world networks to study how interaction structures and their parameters influence the MPGAs, where subpopulations are regarded as nodes and their interaction or migration of elites between subpopulations as edges. After solving the flexible job-shop scheduling problem (FJSP) by MPGAs with different parameters of interaction structures, simulation results were measured by criteria, such as success rate and average optimal value. The analysis reveals that (1) the smaller the average path length (APL) of the network is, the higher the propagation rate will be; (2) the performance of MPGAs increased first and then decreased along with the decrease of APL, indicating that, for better performance, the networks should have a proper APL, which can be adjusted by changing the structural parameters of networks; and (3) because the edge number of small-world networks remains unchanged with different rewiring possibilities of edges, the change in performance indicates that the MPGA can be improved by a more proper interaction structure of subpopulations as other conditions remain unchanged.

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Evolutionary algorithms for solving single- and multiple-objective political redistricting problems: The case study of Poland

Tomczyk,

Kadziński

2024

Applied Soft Computing

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Multiobjective Genetic Algorithms for Reinforcing Equal Population in Congressional Districts

Cited by 4 publications

References 35 publications

Research on the Coordination Model of Passenger Transportation Mode in the Intercity Comprehensive Transportation Corridor

Research on the Coordination Model of Passenger Transportation Mode in the Intercity Comprehensive Transportation Corridor

Multipopulation Genetic Algorithms with Different Interaction Structures to Solve Flexible Job-Shop Scheduling Problems: A Network Science Perspective

Evolutionary algorithms for solving single- and multiple-objective political redistricting problems: The case study of Poland

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