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The continuous optimisation is performed using a successive convex approximation scheme.
Memetic algorithms with an appropriate trade-off between the exploration and exploitation can obtain very good results in continuous optimisation.
This results in a large number of continuous optimisation problems which can be solved very efficiently by a proposed optimisation algorithm that is especially tailored for the problem at hand.
The original Cuckoo Search (CS) was inspired by the breeding behaviour of some cuckoo species and was designed specifically for application in continuous optimisation problems, in which the algorithm had been demonstrated to be effective.
Implementation of Snyman's gradient-based LFOPC optimisation algorithm to the continuous optimisation problem, results in the economic determination of an unambiguous continuous solution, which is then utilised as the starting point for a neighbourhood search within the discrete set of profiles available, to attain the discrete optimum.
The spiral optimisation (SpO) is a multipoint search for continuous optimisation problems.
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The flowsheet structure and its operating conditions are thereby considered as complicating decision variables in an overall non-linear and non-continuous optimisation problem that is addressed with an evolutionary, multi-objective optimisation algorithm.
The TPR data analysis is comprised of two aspects: a discrete model identification and a continuous parameter optimisation.
For both continuous parameter optimisation and discrete parameters with large search ranges, it is practically impossible to choose direct neighbours of the current solution as new candidate solutions due to the vast number of points in the search space.
This is because the above mutation operator was developed for continuous function optimisation, and it does not consider the discrete nature of the qualitative model space.
And, like Kodak, their success came from the continuous execution and optimisation of a single, successful business model.
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