Genetic algorithm encoding representations for graph partitioning problems

Feasibility study of optimization of a genetic algorithm for traffic network division for distributed road traffic simulation

“…The fitness function represents an objective assessment of each individual depending on the solved problem. It is the only part of the genetic algorithm where the knowledge of the problem domain is necessary [8].…”

Issues of Optimization of a Genetic Algorithm for Traffic Network Division using a Genetic Algorithm

“…A single solution of the solved problem is considered to be an individual (usually represented by a vector of binary or integer values). At the start, a set of individuals (so-called initial population) is most often randomly generated (Menouar, 2010). Then, the fitness function is calculated for each individual.…”

“…Then, a number of individuals with highest fitness value are selected as the parents of a new generation. The new generation is created using the selected individuals and the crossover and mutation operators (Menouar, 2010).…”

Suitability of a Genetic Algorithm for Road Traffic Network Division

“…Genetic algorithms (GA) are evolutionary algorithms that mimic natural genetic evolution and selection in nature (Menouar, 2010). Developed by John Holland at the University of Michigan (Holland, 1975), they are widely used for solving of searching and optimization problems in many domains including multi-objective optimization (Farshbaf and Feizi-Darakhshi, 2009).…”

“…In this paper, the suitability of a genetic algorithm (GA) as a part of a method for division of road traffic network is discussed. Genetic algorithms are considered, since they are often employed in both graph partitioning (Menouar, 2010) and multiobjective optimization (Farshbaf and Feizi-Darakhshi, 2009) problems, which are closely associated with the problem of road traffic network division.…”