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Multi-objective optimisation using agent-based modelling
ENGLISH ABSTRACT: It is very seldom that a decision-making problem concerns only a single value or objective. The process of simultaneously optimising two or more con icting objectives is known as multi-objective optimisation (MOO). A number of metaheuristics have been successfully adapted for...
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| Format: | Thesis |
| Language: | en_ZA |
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Stellenbosch : Stellenbosch University
2012
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| _version_ | 1867613924325588992 |
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| access_status_str | Open Access |
| author | Franklin, Chris |
| author2 | Bekker, James F. |
| author_browse | Bekker, James F. Franklin, Chris |
| author_facet | Bekker, James F. Franklin, Chris |
| author_sort | Franklin, Chris |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | ENGLISH ABSTRACT: It is very seldom that a decision-making problem concerns only a single
value or objective. The process of simultaneously optimising two
or more con
icting objectives is known as multi-objective optimisation
(MOO). A number of metaheuristics have been successfully adapted
for MOO. The aim of this study was to investigate the feasibility of
applying an agent-based modelling approach to MOO.
The (s; S) inventory problem was chosen as the application eld for
this approach and Anylogic used as model platform. Agents in the
model were responsible for inventory and sales management, and had
to negotiate with each other in order to nd optimal reorder strategies.
The introduction of concepts such as agent satisfaction indexes,
aggression factors, and recollection ability guided the negotiation process
between the agents.
The results revealed that the agents had the ability to nd good
strategies. The Pareto front generated from their proposed strategies
was a good approximation to the known front. The approach was also
successfully applied to a recognised MOO test problem proving that
it has the potential to solve a variety of MOO problems.
Future research could focus on further developing this approach for
more practical applications such as complex supply chain systems,
nancial models, risk analysis and economics. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/71788 |
| institution | Stellenbosch University (South Africa) |
| language | en_ZA |
| last_indexed | 2026-06-10T12:43:52.525Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2012 |
| publishDateRange | 2012 |
| publishDateSort | 2012 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/71788 Multi-objective optimisation using agent-based modelling Franklin, Chris Bekker, James F. Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering. Multi-objective optimisation Agent-based modelling Inventory problem Agents Anylogic Dissertations -- Industrial engineering Theses -- Industrial engineering ENGLISH ABSTRACT: It is very seldom that a decision-making problem concerns only a single value or objective. The process of simultaneously optimising two or more con icting objectives is known as multi-objective optimisation (MOO). A number of metaheuristics have been successfully adapted for MOO. The aim of this study was to investigate the feasibility of applying an agent-based modelling approach to MOO. The (s; S) inventory problem was chosen as the application eld for this approach and Anylogic used as model platform. Agents in the model were responsible for inventory and sales management, and had to negotiate with each other in order to nd optimal reorder strategies. The introduction of concepts such as agent satisfaction indexes, aggression factors, and recollection ability guided the negotiation process between the agents. The results revealed that the agents had the ability to nd good strategies. The Pareto front generated from their proposed strategies was a good approximation to the known front. The approach was also successfully applied to a recognised MOO test problem proving that it has the potential to solve a variety of MOO problems. Future research could focus on further developing this approach for more practical applications such as complex supply chain systems, nancial models, risk analysis and economics. AFRIKAANSE OPSOMMING: Daar is weinig besluitnemingsprobleme waar slegs 'n enkele waarde of doelwit ter sprake is. Die proses waar twee of meer doelwitte, wat in konflik staan met mekaar, gelyktydig optimiseer word, staan bekend as multi-doelwit optimisering (MOO). 'n Aantal metaheuristieke is al suksesvol aangepas vir MOO. Die doelwit van hierdie studie was om ondersoek in te stel na die lewensvatbaarheid van die toepassing van 'n agent gebasseerde modelerings benadering tot MOO. As toepassingsveld vir hierdie benadering was die (s; S) voorraad probleem gekies en Anylogic was gebruik as model platform. In die model was agente verantwoordelik vir voorraad- en verkope bestuur. Hulle moes onderling met mekaar onderhandel om die optimale bestelling strategiee te verkry. Konsepte soos agentbevrediging, aggressie faktore en herinneringsvermoens is ingestel om die onderhandeling tussen die agente te bewerkstellig. Die resultate het gewys dat die agente oor die vermoe beskik om met goeie strategiee vorendag te kom. Die Pareto fronte wat gegenereer is deur hul voorgestelde strategiee was 'n goeie benadering tot die bekende front. Die benadering was ook suksesvol toegepas op 'n erkende MOO toets-probleem wat bewys het dat dit oor die potensiaal beskik om 'n verskeidenheid van MOO probleme op te los. Toekomstige navorsing kan daarop fokus om hierdie benadering verder te ontwikkel vir meer praktiese toepassings soos komplekse voorsieningskettingstelsels, finnansiele modelle, risiko-analises en ekonomie. 2012-11-29T12:19:42Z 2012-12-12T08:11:26Z 2012-11-29T12:19:42Z 2012-12-12T08:11:26Z 2012-12 Thesis http://hdl.handle.net/10019.1/71788 en_ZA Stellenbosch University 94 p. : ill. application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | Multi-objective optimisation Agent-based modelling Inventory problem Agents Anylogic Dissertations -- Industrial engineering Theses -- Industrial engineering Franklin, Chris Multi-objective optimisation using agent-based modelling |
| title | Multi-objective optimisation using agent-based modelling |
| title_full | Multi-objective optimisation using agent-based modelling |
| title_fullStr | Multi-objective optimisation using agent-based modelling |
| title_full_unstemmed | Multi-objective optimisation using agent-based modelling |
| title_short | Multi-objective optimisation using agent-based modelling |
| title_sort | multi objective optimisation using agent based modelling |
| topic | Multi-objective optimisation Agent-based modelling Inventory problem Agents Anylogic Dissertations -- Industrial engineering Theses -- Industrial engineering |
| url | http://hdl.handle.net/10019.1/71788 |
| work_keys_str_mv | AT franklinchris multiobjectiveoptimisationusingagentbasedmodelling |