Research on discrete wolf pack algorithm of mutiple choice knapsack problem

DONG Ya-ke; DU Jun; LI Bo; DING Chao

doi:10.13873/J.1000-9787(2015)06-0021-03

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Research on discrete wolf pack algorithm of mutiple choice knapsack problem

更新时间：2025-09-11

- Research on discrete wolf pack algorithm of mutiple choice knapsack problem
- Vol. 34, Issue 6, Pages: 21-23+26(2015)
- 作者机构：
  
  空军工程大学航空航天工程学院
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2015)06-0021-03
  CLC： TP18
- Published：2015
- 稿件说明：
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[1]董亚科,杜军,李博,丁超.多选择背包问题离散狼群算法研究[J].传感器与微系统,2015,34(06):21-23+26.

DONG Ya-ke, DU Jun, LI Bo, et al. Research on discrete wolf pack algorithm of mutiple choice knapsack problem[J]. 2015, 34(6): 21-23+26.
[1]董亚科,杜军,李博,丁超.多选择背包问题离散狼群算法研究[J].传感器与微系统,2015,34(06):21-23+26. DOI： 10.13873/J.1000-9787(2015)06-0021-03.

DONG Ya-ke, DU Jun, LI Bo, et al. Research on discrete wolf pack algorithm of mutiple choice knapsack problem[J]. 2015, 34(6): 21-23+26. DOI： 10.13873/J.1000-9787(2015)06-0021-03.

摘要

狼群算法是一种通过模拟狼群的捕食行为和猎物分配方式提出的群体智能算法

为求解复杂组合优化问题提供了一种新的思路。目前狼群算法不能解决离散问题

以NP难中的经典问题——多选择背包问题的求解为研究对象

设计了基于离散空间的狼群算法。对于离散空间的狼群算法

通过将人工狼编码

重新设计了狼群的游走、奔袭和围捕过程

并设计了三个过程中的步长。把学习机制引入离散狼群算法

实现了人工狼之间的交流

且确立了自适应步长公式。结果表明:离散狼群算法成功实现了对离散问题的求解

为组合优化问题的求解提供了新方法。

Abstract

Wolf pack algorithm is an swarm intelligence algorithm which simulates predation behavior and prey allocation mode of wolf pack

which provides a new method to solve complex combinatorial optimization problems.Wolf pack algorithm can’t solve discrete problems

solving of classical NP-hard problem

multiple choice knapsack problem is research goal

design a wolf pack algorithm based on discrete space. Through artificial wolf coding

redesign wolves

migration

long-range raid

and round up process

and stepsize of three process is designed. The learning mechanism is introduced into discrete wolf pack algorithm（ DWPA）

which realizes communication between artificial wolves and establish the adaptive step length formula. The results show that DWPA not only implements discrete problem solving

but also provide new method for solving combinatorial optimization problem.

关键词

Keywords

references

一种新的群体智能算法——狼群算法 [J]. 吴虎胜,张凤鸣,吴庐山. 系统工程与电子技术 . 2013(11)

粒子群优化算法求解多选择背包问题 [J]. 陈娟,王志刚,夏慧明. 价值工程 . 2012(05)

多选择背包问题的快速求解算法 [J]. 鲍江宏,杨启贵. 华南理工大学学报(自然科学版) . 2009(04)

反馈混沌遗传算法及其在约束优化中的应用 [J]. 孙有发,高京广,张成科,邓飞其. 华南理工大学学报(自然科学版) . 2007(01)

多重群体遗传算法在多选择背包问题中的应用 [J]. 叶宇风. 计算机工程与设计 . 2005(12)

改进遗传算法及其在背包问题中的应用 [J]. 苑立伟,刘付显,赵保军. 系统工程与电子技术 . 2005(04)

遗传算法与工程优化[M]. 清华大学出版社 , [日]玄光男,[日]程润伟著, 2004

Dynamic-objective particle swarm optimization for constrained optimization problems [J] . Haiyan Lu,Weiqi Chen. Journal of Combinatorial Optimization . 2006 (4)

Unbounded knapsack problem: Dynamic programming revisited [J] . R. Andonov,V. Poirriez,S. Rajopadhye. European Journal of Operational Research . 2000 (2)

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