Multi-objective optimisation of web business processes

Show simple item record Tiwari, Ashutosh - Turner, Christopher - Ball, Peter D. - Vergidis, Kostas -
dc.contributor.editor Deb, K. -
dc.contributor.editor Bhattacharya, A. -
dc.contributor.editor Chakroborty, P. -
dc.contributor.editor Dutta, J. -
dc.contributor.editor Gupta, S. K. -
dc.contributor.editor Jain, A. -
dc.contributor.editor Aggarwal, V. -
dc.contributor.editor Branke, J. -
dc.contributor.editor Louis, S. J. -
dc.contributor.editor Tan, K. C. - 2011-10-11T23:07:45Z 2011-10-11T23:07:45Z 2010-12-31T00:00:00Z -
dc.identifier.citation Ashutosh Tiwari, Christopher Turner, Peter Ball and Kostas Vergidis., Multi-objective optimisation of web business processes. Simulated Evolution and Learning, Lecture Notes in Computer Science, 2010, Volume 6457/2010, pp573-577,
dc.identifier.isbn 978-3-642-17297-7 -
dc.identifier.uri -
dc.description.abstract 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. en_UK
dc.title Multi-objective optimisation of web business processes en_UK
dc.type Book chapter -

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