Improved Ant Colony Optimization to Multi-objective Resource Allocation Problems

LU Xiu-ying; CUI Xing-kai; HUO Xin-li

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Improved Ant Colony Optimization to Multi-objective Resource Allocation Problems

更新时间：2026-09-04

- Improved Ant Colony Optimization to Multi-objective Resource Allocation Problems
- Vol. 28, Issue 10, Pages: 87-90(2011)
- 作者机构：
  
  河北农业大学机构教务处,河北,保定,071001
- 作者简介：
- 基金信息：
- DOI：
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- Published：2011
- 稿件说明：
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路秀英, 崔兴凯, 霍新丽. 求解多目标资源分配问题的改进蚁群优化算法[J]. 微电子学与计算机, 2011, 28(10): 87-90.

LU Xiu-ying, CUI Xing-kai, HUO Xin-li. Improved Ant Colony Optimization to Multi-objective Resource Allocation Problems[J]. 2011, 28(10): 87-90.
路秀英, 崔兴凯, 霍新丽. 求解多目标资源分配问题的改进蚁群优化算法[J]. 微电子学与计算机, 2011, 28(10): 87-90. DOI：

LU Xiu-ying, CUI Xing-kai, HUO Xin-li. Improved Ant Colony Optimization to Multi-objective Resource Allocation Problems[J]. 2011, 28(10): 87-90. DOI：

摘要

多目标资源分配问题就是将有限资源分配到不同事件来获得预期目标.建立了多目标资源分配问题的数学模型

提出了一种有效求解该问题的改进蚁群优化算法:设计了一种多目标资源分配问题的可行方案构建机制

定义了蚁群优化算法中的信息素形式及其更新方式

提出了一种新的概率选择形式;通过以上改进有效地提高了蚁群优化方法的效率.为了验证此方法的有效性

将蚁群优化方法与混合遗传算法的实验结果进行了对比分析

证明此方法优于混合遗传算法.

Abstract

The multi-objective resource allocation problem addresses the important issue which seeks to find the expected objectives by allocating the limited amount of resource to various activates.The mathematical model of multi-objective resource allocation problems is proposed

and an improved ant colony optimization algorithm is proposed to multi-objective resource allocation problems.In the proposed approach

the feasible solution construction mechanism is designed firstly

both the pheromone form and its updating rule are designed and a new probability selection method is proposed.All these works improve the performance of ant colony optimization algorithm.Effectiveness and efficiency of this algorithm was validated by comparing the result of this method with a hybrid genetic algorithm.

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