Deleted Journal, Journal Year: 2025, Volume and Issue: 3(2), P. 74 - 86
Published: March 3, 2025
This study presents a comprehensive analysis of recent studies that explore the application genetic algorithms (GAs) for optimizing solutions to 0/1 Knapsack Problem (KP). The Problem, classic combinatorial optimization challenge, involves selecting subset items with given weights and values maximize total value without exceeding specified weight limit. Genetic algorithms, inspired by principles natural selection genetics, have emerged as powerful heuristic tackling this NP-hard problem. Our review synthesizes findings from contemporary research, highlighting effectiveness various GA approaches, including standard GAs, hybrid models, enhanced techniques incorporating local search other strategies. We evaluate performance metrics, computational efficiency, solution quality achieved these methods. Additionally, we discuss strengths limitations GAs in addressing providing insights into their practical applications potential improvements. paper concludes recommendations future research directions, aiming advance state-of-the-art algorithm-based Problem.
Language: Английский