Genetic Algorithm Based on Active Evolution for Large Scale 0-1 Knapsack Problem

In order to overcome the problems in resolving large scale 0-1 knapsack problem with genetic algorithm,this paper introduces the directed mutation into the genetic algorithm and presents an active-evolution-based genetic algorithm(AEBGA) for the 0-1 knapsack problem.The algorithm uses probability coding mechanism to construct seed individual,which is used to generate individuals in each generation.In each generation,inducement is generated and used for seed individual evaluation.SGA,GQA and AEBGA are applied to solve large scale 0-1 knapsack problem and experiment results show that AEBGA has good ability of global optimization and high efficiency.