Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
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...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
Department of Chemical Engineering
2024
|
| Subjects: | |
| Tags: |
No Tags, Be the first to tag this record!
|
| Summary: | 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. |
|---|