Optimizing task allocation in workflow system based on ant colony optimization

被引：0

作者：

Lyu L. ^{[1
]}

Hu H. ^{[1
,2
]}

Li Z. ^{[1
]}

Chen J. ^{[1
]}

Hu H. ^{[1
,2
]}

机构：

[1] College of Computer Science, Hangzhou Dianzi University, Hangzhou

[2] State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing

来源：

Hu, Haiyang (huhaiyang@hdu.edu.cn) | 1723年 / CIMS卷 / 24期

基金：

中国国家自然科学基金;

关键词：

Ant colony; Compatibility; Task assignment; Workflow;

D O I：

10.13196/j.cims.2018.07.014

中图分类号：

学科分类号：

摘要：

Factors that affect the performance efficiency of workflow system include not only the capability of each executor, but also the degree of understanding between collaborators. At present, there is no uniform standard for measuring this degree of tacit understanding. The degree of tacit understanding between the performers was defined as the cooperative compatibility, and the mathematical statistic method with the nature of normal distribution were used to measure the fuzzy cooperative compatibility as the specific data, and the proof method was given. Based on ant colony algorithm, an optimizing task allocation was presented by taking into account both the cooperative compatibility and the workload of each executors, which could improve the execution efficiency of the while process instance. The performance of the proposed algorithm was evaluated by comparing with the three algorithms. © 2018, Editorial Department of CIMS. All right reserved.

引用

页码：1723 / 1735

页数：12

共 14 条

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