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Metaheuristics for petrochemical blending problems
ENGLISH ABSTRACT: The main aim in blending problems is to determine the best blend of available ingredients to form a certain quantity of product(s). This product should adhere to strict speci cations. In this study the best blend means the least-cost blend of ingredients (input) required to mee...
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| Format: | Thesis |
| Language: | English |
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Stellenbosch : University of Stellenbosch
2010
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| Summary: | ENGLISH ABSTRACT: The main aim in blending problems is to determine the best blend of available ingredients to form a
certain quantity of product(s). This product should adhere to strict speci cations. In this study the
best blend means the least-cost blend of ingredients (input) required to meet a minimum level of product
(output) speci cations. The most prevalent tools to solve blending problems in the industry are by means
of spreadsheets, simulators and mathematical programming. While there may be considerable bene t in
using these types of tools to identify potential opportunities and infeasibilities, there is a potentially even
greater bene t in searching automitically for alternative solutions that are more economical and e cient.
Heuristics and metaheuristics are presented as useful alternative solution approaches.
In this thesis di erent metaheuristic techniques are developed and applied to three typical blending
problems of varied size taken from the petrochemical industry. a fourth instance of real life size is also
introduced. Heuristics are developed intuitively, while metaheuristics are adopted from the literature.
Random search techniques, such as blind random search and local random search, deliver fair results.
Within the class of genetic algorithms the best results for all three problems were obtained using ranked
tness assignment with tournament selection of individuals. Good results are also obtained by means of
tabu search approaches - even considering the continuous nature of these problems. A simulated annealing
approach also yielded fair results. A comparison of the results of the di erent approaches shows that
the tabu search technique delivers the best result with respect to solution quality and execution time for
all three the problems under consideration. Simulated annealing, however, delivers the best result with
respect to solution quality and execution time for the introduced real life size problem. |
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