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Multi-agent analysis of industrial networks : a South African bio-energy case study
Industrial networks are complex structures consisting of multiple interacting enterprises, differing in nature, each with independent (often conflicting) objectives, producing numerous, possibly competing products. These networks play an important role in meeting basic human needs and contributing t...
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| Format: | Thesis |
| Language: | English |
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Department of Chemical Engineering
2024
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| _version_ | 1867613212466216960 |
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| access_status_str | Open Access |
| author | Malan, Rene |
| author2 | Petrie, Jim |
| author_browse | Malan, Rene Petrie, Jim |
| author_facet | Petrie, Jim Malan, Rene |
| author_sort | Malan, Rene |
| collection | Thesis |
| description | Industrial networks are complex structures consisting of multiple interacting enterprises, differing in nature, each with independent (often conflicting) objectives, producing numerous, possibly competing products. These networks play an important role in meeting basic human needs and contributing to economic prosperity through generation, manufacture and distribution of goods and services. Design of a network to achieve more sustainable business practice requires an understanding of how its structure and function affect its economiC, environmental and social performance. In this thesis it is argued that this understanding can be gained through modelling and simulation of such networks, where existing toolkits include simulators and/or optimisers, as well as an array of "soft systems" approaches, including multi-criteria decision analysis (MCDA). An agent-based simulation-optimisation approach was developed to capture the complexity associated with modelling of industrial networks, including the decision-making process followed by each enterprise, the responsiveness and interplay between the enterprises and the evolution and performance of the network over time. This modelling approach was applied to a case study network associated with generation of electricity from biomass in the province of kwaZulu-Natal, South Africa. The network includes sugar and paper and pulp mills, the South African power utility and independent power producers. The decision-making criteria of the enterprises and the key performance indicators of the network were both measured by economic (cost and NPV respectively), environmental (C02 emissions) and social (electrification of rural communities) factors. The sensitivity of the structure and function of the network to changes in network effects (carbon credits selling price) and enterprise behaviour (decision and risk policies) was tested. It was found that changes in enterprise behaviour had the greatest influence on the structure and functioning of the network, with changes in decision policy having a greater influence than changes in risk policy. From this case study it is concluded that although each network presents custom complexities and uncertainties, the modelling approach developed in this thesis does provide a platform that allows designers, analysts and decision-makers to take into account relevant enterprise and network characteristics. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/39971 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:32:33.381Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | Department of Chemical Engineering |
| publisherStr | Department of Chemical Engineering |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/39971 Multi-agent analysis of industrial networks : a South African bio-energy case study Malan, Rene Petrie, Jim Chemical Engineering Industrial networks are complex structures consisting of multiple interacting enterprises, differing in nature, each with independent (often conflicting) objectives, producing numerous, possibly competing products. These networks play an important role in meeting basic human needs and contributing to economic prosperity through generation, manufacture and distribution of goods and services. Design of a network to achieve more sustainable business practice requires an understanding of how its structure and function affect its economiC, environmental and social performance. In this thesis it is argued that this understanding can be gained through modelling and simulation of such networks, where existing toolkits include simulators and/or optimisers, as well as an array of "soft systems" approaches, including multi-criteria decision analysis (MCDA). An agent-based simulation-optimisation approach was developed to capture the complexity associated with modelling of industrial networks, including the decision-making process followed by each enterprise, the responsiveness and interplay between the enterprises and the evolution and performance of the network over time. This modelling approach was applied to a case study network associated with generation of electricity from biomass in the province of kwaZulu-Natal, South Africa. The network includes sugar and paper and pulp mills, the South African power utility and independent power producers. The decision-making criteria of the enterprises and the key performance indicators of the network were both measured by economic (cost and NPV respectively), environmental (C02 emissions) and social (electrification of rural communities) factors. The sensitivity of the structure and function of the network to changes in network effects (carbon credits selling price) and enterprise behaviour (decision and risk policies) was tested. It was found that changes in enterprise behaviour had the greatest influence on the structure and functioning of the network, with changes in decision policy having a greater influence than changes in risk policy. From this case study it is concluded that although each network presents custom complexities and uncertainties, the modelling approach developed in this thesis does provide a platform that allows designers, analysts and decision-makers to take into account relevant enterprise and network characteristics. 2024-06-19T09:22:59Z 2024-06-19T09:22:59Z 2007 2024-06-19T09:11:37Z Thesis / Dissertation Masters MSc http://hdl.handle.net/11427/39971 eng application/pdf Department of Chemical Engineering Faculty of Engineering and the Built Environment |
| spellingShingle | Chemical Engineering Malan, Rene Multi-agent analysis of industrial networks : a South African bio-energy case study |
| thesis_degree_str | Master's |
| title | Multi-agent analysis of industrial networks : a South African bio-energy case study |
| title_full | Multi-agent analysis of industrial networks : a South African bio-energy case study |
| title_fullStr | Multi-agent analysis of industrial networks : a South African bio-energy case study |
| title_full_unstemmed | Multi-agent analysis of industrial networks : a South African bio-energy case study |
| title_short | Multi-agent analysis of industrial networks : a South African bio-energy case study |
| title_sort | multi agent analysis of industrial networks a south african bio energy case study |
| topic | Chemical Engineering |
| url | http://hdl.handle.net/11427/39971 |
| work_keys_str_mv | AT malanrene multiagentanalysisofindustrialnetworksasouthafricanbioenergycasestudy |