Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.501666
Title: Global optimisation for modular process design
Author: Balendra, Sujan
Awarding Body: University College London (University of London)
Current Institution: University College London (University of London)
Date of Award: 2007
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Abstract:
The aim of this thesis is to investigate methods for allowing modular process design and simulation systems to rigorously find globally optimal solutions. Sequential Modular Flowsheets are still used by many companies for process design even though they do not use global optimisation. Applying global optimisation to a process flowsheet in the early stages of the design will have significant positive impacts on profitability. In order to maintain a competitive edge in the practical business world it is critical to optimise new designs and operations in manufacturing plants. Significant improvements in finding the global optimum are shown using basic interval contraction when solving mathematical problems with equality constraints. Developments were made to fixed point type contractors to further improve computational efficiency to a set of mathematical test problems containing constraints. The idea and development of contraction was taken forward to modular flowsheets. Global optimisation algorithms have been developed for solving modular flowsheets to involve contractors. The Algorithm was tested to draw conclusions about the computational efficiency with and without the basic contractors. A global optimisation algorithm to find all the global solutions to modular flowsheeting problem was devised and tested. Different interval model formulation of flowsheeting problems were constructed to investigate the computational efficiency for interval global optimisation algorithms and the interval contraction techniques were investigated for every type of formulation.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.501666  DOI: Not available
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