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|Document Type: ||Book chapter|
|Title: ||Multi-objective optimisation of web business processes|
|Authors: ||Tiwari, Ashutosh|
Ball, Peter D.
|Issue Date: ||2010|
|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,|
|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.|
|Appears in Collections:||Staff publications - School of Applied Sciences|
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