.png){kind=icon}
返回
An Improved Shuffled Frog-Leaping Algorithm to Solving 0-1 Knapsack Problem
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2024.3424415.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
To address the problems of slow convergence, low search accuracy, and easy fall into local optimum, and generating a large number of infeasible solutions when solving the 0-1 Knapsack Problem, which makes it difficult to obtain the optimal solution scheme, in this paper, we present a greedy induced mutation method for locally optimal solutions, namely, an improved Shuffled Frog Leaping Algorithm (Shuffled Frog Leaping Algorithm based on Greedy Algorithm and Mutation, SFLA-GA-M). First, the proposed algorithm adjusts the population generation of individuals in the SFLA to avoid infeasible solutions, thereby optimizing the local update strategy. Secondly, an induced mutation mechanism that incorporates both greedy algorithms and genetic algorithms is introduced to enhance the search accuracy of the algorithm. Finally, ten classical 0-1 Knapsack Problem cases were selected to prove the feasibility and robustness of the proposed SFLA-GA-M by comparing with other two SFLA variants, which are MDSFLA, DSFLA. Meanwhile, to further verify the performance of the SFLA-GA-M, two classical 0-1 KPs with multi-dimensional test cases were introduced by compared with other five algorithm: DEA, PSO, GA, BMA and IFMA, respectively. The experimental results show that SFLA-GA-M has achieved stronger convergence and stability compared to DEA, PSO, and GA, and it has displayed better search efficiency and a superior global search capability than BMA and IFMA in solving large-sized 0-1 Knapsack Problem.
Keyword:
Statistics
Social factors
Optimization
Mathematical models
Genetic algorithms
Search problems
Heuristic algorithms
Shuffled frog leaping algorithm
genetic algorithm
mutation
0-1 knapsack problem
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
A Review on Swarm Intelligence and Evolutionary Algorithms for Solving Flexible Job Shop Scheduling Problems求解柔性作业车间调度问题的群体智能和进化算法综述
OAAI
OAAI分享收藏Knapsack problems - An overview of recent advances. Part I: Single knapsack problems背包问题——最新进展概述。第一部分: 单背包问题OAAI
OAAI分享收藏An Improved Cuckoo Search Algorithm Utilizing Nonlinear Inertia Weight and Differential Evolution for Function Optimization Problem.png)
IEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAI分享收藏Knapsack problems - An overview of recent advances. Part II: Multiple, multidimensional, and quadratic knapsack problems背包问题-最新进展概述。第二部分: 多重、多维和二次背包问题OAAI
OAAI分享收藏An Approach for Optimal Allocation of Safety Resources: Using the Knapsack Problem to Take Aggregated Cost-Efficient Preventive MeasuresRISK ANALYSIS
RISK ANALYSISIF3.3
PREAI
分享收藏
查看更多内容