An improved ant colony algorithm to solve knapsack problem

被引：0
|
作者：
Li Shuang [1 ,2 ]
Wang Shuliang [3 ]
Zhang Qiuming [1 ]
机构：
[1] China Univ Geosci, Sch Comp, Wuhan 430074, Peoples R China
[2] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430072, Peoples R China
[3] Wuhan Univ, Int Sch Software, Wuhan 430072, Peoples R China
来源：
GEOINFORMATICS 2006: REMOTELY SENSED DATA AND INFORMATION | 2006年 / 6419卷
关键词：
ant colony optimization algorithm; Knapsack Problem; evolutionary computing;
D O I：
10.1117/12.713269
中图分类号：
TP7 [遥感技术];
学科分类号：
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要：
Ant colony optimization algorithm is a novel simulated evolutionary algorithm, which provides a new method for complicated combinatorial optimization problems. In this paper the algorithm is used for solving the knapsack problem. It is improved in selection strategy and information modification, so that it can not easily run into the local optimum and can converge at the global optimum. The experiments show the robustness and the potential power of this kind of meta heuristic algorithm.
引用
下载
收藏
页数：7
相关论文
共 50 条
  • [31] Traveling salesman problem based on improved ant colony algorithm
    Zhang Hui
    Wang Xi-huai
    Xiao Jian-mei
    Proceedings of the 2007 Chinese Control and Decision Conference, 2007, : 492 - +
  • [32] Application of improved ant colony algorithm in vehicle scheduling problem
    Wang Rui
    Wang Jinguo
    Wang Na
    PROCEEDINGS OF THE 2015 JOINT INTERNATIONAL MECHANICAL, ELECTRONIC AND INFORMATION TECHNOLOGY CONFERENCE (JIMET 2015), 2015, 10 : 656 - 659
  • [33] An Improved Ant Colony Algorithm
    Zhang Xin
    Zhou Yu-zhong
    Fang Ping
    2008 INTERNATIONAL CONFERENCE ON MULTIMEDIA AND INFORMATION TECHNOLOGY, PROCEEDINGS, 2008, : 98 - 100
  • [34] Solving 0-1 Knapsack Problem Based on Immune Clonal Algorithm and Ant Colony Algorithm
    Zhao Fang
    Ma Yu-Lei
    Zhang Jun-Peng
    PROCEEDINGS OF THE 2012 INTERNATIONAL CONFERENCE ON COMMUNICATION, ELECTRONICS AND AUTOMATION ENGINEERING, 2013, 181 : 1047 - +
  • [35] An improved genetic algorithm based approach to solve constrained knapsack problem in fuzzy environment
    Changdar, Chiranjit
    Mahapatra, G. S.
    Pal, Rajat Kumar
    EXPERT SYSTEMS WITH APPLICATIONS, 2015, 42 (04) : 2276 - 2286
  • [36] Ant Colony Optimization Algorithm for the 0-1 Knapsack Problem Based on Genetic Operators
    Hu, Zhijun
    Li, Rong
    FRONTIERS OF MANUFACTURING SCIENCE AND MEASURING TECHNOLOGY, PTS 1-3, 2011, 230-232 : 973 - 977
  • [37] Hybrid optimization algorithm of ant colony optimization and Lagrangian relaxation for solving multidimensional knapsack problem
    Ren Z.-G.
    Zhao S.-Y.
    Huang S.-S.
    Liang Y.-S.
    Ren, Zhi-Gang (renzg@mail.xjtu.edu.cn), 1600, Northeast University (31): : 1178 - 1184
  • [38] A new ant colony optimization applied for the multidimensional knapsack problem
    Kong, Min
    Tian, Peng
    SIMULATED EVOLUTION AND LEARNING, PROCEEDINGS, 2006, 4247 : 142 - 149
  • [39] Improved dynamic adaptive ant colony optimization algorithm to solve pipe routing design
    Liu, Chao
    Wu, Lei
    Huang, Xiaodong
    Xiao, Wensheng
    KNOWLEDGE-BASED SYSTEMS, 2022, 237
  • [40] Ant colony optimization for multiple knapsack problem and model bias
    Fidanova, S
    NUMERICAL ANALYSIS AND ITS APPLICATIONS, 2005, 3401 : 280 - 287
12345