Multi-Objective Optimisation of Web Business Processes

被引:0
|
作者
Tiwari, Ashutosh [1 ]
Turner, Christopher [1 ]
Ball, Peter [1 ]
Vergidis, Kostas [1 ]
机构
[1] Cranfield Univ, Decis Engn Ctr, Cranfield MK43 0AL, Beds, England
来源
SIMULATED EVOLUTION AND LEARNING | 2010年 / 6457卷
基金
英国工程与自然科学研究理事会;
关键词
Multi-objective optimisation; Business Process; EMOA; Web services;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper proposes an approach for the optimisation of web business processes using multi-objective evolutionary computing. Business process optimisation is considered as the problem of constructing feasible business process designs with optimum attribute values such as duration and cost. This optimisation framework involves the application of a series of Evolutionary Multi-objective Optimisation Algorithms (EMOAs) in an attempt to generate a series of diverse optimised business process designs for given requirements. The optimisation framework is tested to validate the framework's capability in capturing, composing and optimising business process designs constituted of web services. The results from the web business process optimisation scenario, featured in this paper, demonstrate that the framework can identify business process designs with optimised attribute values.
引用
收藏
页码:573 / 577
页数:5
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