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This study explores the application of genetic algorithms (GAs) in optimizing facility layout design.Traditional facility layout design involves arranging physical elements within a space to enhance efficiency and productivity.However, manual methods often fail to consider all constraints and variables, leading to suboptimal solutions.Genetic algorithms offer a promising approach by mimicking the process of natural selection to iteratively evolve layouts towards optimal configurations.This paper reviews the principles of genetic algorithms and their adaptation to facility layout problems.It discusses key components such as chromosome representation, fitness evaluation, selection mechanisms, crossover, and mutation operators
Gowda et al. (Wed,) studied this question.