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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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| _version_ | 1867613763118563328 |
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| access_status_str | Open Access |
| author | Venter, Lieschen |
| author2 | Visagie, S. E. |
| author_browse | Venter, Lieschen Visagie, S. E. |
| author_facet | Visagie, S. E. Venter, Lieschen |
| author_sort | Venter, Lieschen |
| collection | Thesis |
| dc_rights_str_mv | University of Stellenbosch |
| description | 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. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/4180 |
| institution | Stellenbosch University (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:41:18.607Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2010 |
| publishDateRange | 2010 |
| publishDateSort | 2010 |
| publisher | Stellenbosch : University of Stellenbosch |
| publisherStr | Stellenbosch : University of Stellenbosch |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/4180 Metaheuristics for petrochemical blending problems Venter, Lieschen Visagie, S. E. University of Stellenbosch. Faculty of Economic and Management Sciences. Dept. of Logistics. Petrochemical blending Metaheuristics Heuristics Search techniques Dissertations -- Logistics Theses -- Logistics Logistics 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. AFRIKAANSE OPSOMMING: Die hoofdoelwit met die oplos van mengprobleme is om die beste mengsel van beskikbare bestandele te bepaal om 'n sekere hoeveelheid produk(te) te vervaardig. Die produk moet aan streng vereistes voldoen. Die beste kombinasie is die goedkoopste kombinasie van bestandele (toevoer) wat aan die minimum produkvereistes (afvoer) voldoen. Die algemeenste benaderings waarmee mengprobleme in die industrie opgelos word, is met behulp van sigblaaie, simulasies en wiskundige programmering. Hierdie metodes is baie nuttig om belowende oplossings of ontoelaatbaarhede te identi seer, maar dit kan potensieel meer voordelig wees om metodes te gebruik wat sistematies meer ekonomiese en e ektiewe oplossings vind. Heuristieke en metaheuristieke word as goeie alternatiewe oplossingsbenaderings aangebied. In hierdie tesis word verskillende metaheuristiekbenaderings toegepas op drie tipiese mengprobleme van verskillende groottes wat vanuit die petrochemiese industrie spruit. 'n Vierde geval met realistiese (regte wêreld) grootte word ook aangebied. Heuristieke word volgens intuïsie ontwikkel terwyl metaheuristieke aangepas word vanuit die literatuur. Lukrake soektegnieke soos die blinde lukrake soektegniek en die plaaslike lukrake soektegniek lewer redelike resultate. Binne die klas van genetiese algoritmes word die beste resultate gelewer wanneer die algoritme met 'n kombinasie van rangorde ksheidstoekenning en toernooiseleksie van individue geïmplimenteer word. Goeie resultate word ook verkry met behulp van tabusoektogbenaderings ten spyte van die kontinue aard van hierdie probleme. Gesimuleerde tempering lewer ook redelike resultate. 'n Vergelyking van die resultate van die verskillende tegnieke toon dat die tabusoektogtegniek die beste resultate met betrekking tot die kwaliteit van die oplossing sowel as uitvoertyd lewer. Gesimuleerde tempering lewer egter die beste resultate met betrekking tot die kwaliteit van die oplossing sowel as uitvoertyd vir die voorgestelde realistiese grootte probleem. Masters 2010-02-18 2010-02-18T10:46:30Z 2010-03 Thesis http://hdl.handle.net/10019.1/4180 en University of Stellenbosch 124 p. : ill. application/pdf Stellenbosch : University of Stellenbosch |
| spellingShingle | Petrochemical blending Metaheuristics Heuristics Search techniques Dissertations -- Logistics Theses -- Logistics Logistics Venter, Lieschen Metaheuristics for petrochemical blending problems |
| title | Metaheuristics for petrochemical blending problems |
| title_full | Metaheuristics for petrochemical blending problems |
| title_fullStr | Metaheuristics for petrochemical blending problems |
| title_full_unstemmed | Metaheuristics for petrochemical blending problems |
| title_short | Metaheuristics for petrochemical blending problems |
| title_sort | metaheuristics for petrochemical blending problems |
| topic | Petrochemical blending Metaheuristics Heuristics Search techniques Dissertations -- Logistics Theses -- Logistics Logistics |
| url | http://hdl.handle.net/10019.1/4180 |
| work_keys_str_mv | AT venterlieschen metaheuristicsforpetrochemicalblendingproblems |