Sensitivity Analysis of the i* Optimisation Model
Requirement elicitation is an important activity in early requirement engineering. Several well-known approaches and goal models have been developed to deal with requirement elicitation. The i* goal model is used to represent the socio-technical domains and can be used for analysis in early requirem...
| Main Authors: | , , |
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| Format: | Journal Article |
| Published: |
Academy Publisher
2016
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| Online Access: | http://hdl.handle.net/20.500.11937/14410 |
| _version_ | 1848748615674101760 |
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| author | Subramanian, C. Krishna, Aneesh Kaur, Arshinder |
| author_facet | Subramanian, C. Krishna, Aneesh Kaur, Arshinder |
| author_sort | Subramanian, C. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Requirement elicitation is an important activity in early requirement engineering. Several well-known approaches and goal models have been developed to deal with requirement elicitation. The i* goal model is used to represent the socio-technical domains and can be used for analysis in early requirement analysis. The elicitation process is complicated by the incomplete and imprecise input data available for analysis. Imprecise and unavailable data can be captured by fuzzy logic and then it can be managed by the popular operation research techniques known as optimisation. This paper presents a formal multi-objective optimisation model, for the i* framework, with regard to requirement elicitation. The optimisation model has the capacity to handle large and complex systems. The optimisation model has been expanded to include sensitivity analysis, in order to facilitate useful information on input data for the requirement analyst. The proposed approach is explained using the London Ambulance System case study and is evaluated using a simulation based analysis. |
| first_indexed | 2025-11-14T07:07:52Z |
| format | Journal Article |
| id | curtin-20.500.11937-14410 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:07:52Z |
| publishDate | 2016 |
| publisher | Academy Publisher |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-144102017-09-13T14:04:53Z Sensitivity Analysis of the i* Optimisation Model Subramanian, C. Krishna, Aneesh Kaur, Arshinder Requirement elicitation is an important activity in early requirement engineering. Several well-known approaches and goal models have been developed to deal with requirement elicitation. The i* goal model is used to represent the socio-technical domains and can be used for analysis in early requirement analysis. The elicitation process is complicated by the incomplete and imprecise input data available for analysis. Imprecise and unavailable data can be captured by fuzzy logic and then it can be managed by the popular operation research techniques known as optimisation. This paper presents a formal multi-objective optimisation model, for the i* framework, with regard to requirement elicitation. The optimisation model has the capacity to handle large and complex systems. The optimisation model has been expanded to include sensitivity analysis, in order to facilitate useful information on input data for the requirement analyst. The proposed approach is explained using the London Ambulance System case study and is evaluated using a simulation based analysis. 2016 Journal Article http://hdl.handle.net/20.500.11937/14410 10.17706/jsw.11.1.10-26 Academy Publisher restricted |
| spellingShingle | Subramanian, C. Krishna, Aneesh Kaur, Arshinder Sensitivity Analysis of the i* Optimisation Model |
| title | Sensitivity Analysis of the i* Optimisation Model |
| title_full | Sensitivity Analysis of the i* Optimisation Model |
| title_fullStr | Sensitivity Analysis of the i* Optimisation Model |
| title_full_unstemmed | Sensitivity Analysis of the i* Optimisation Model |
| title_short | Sensitivity Analysis of the i* Optimisation Model |
| title_sort | sensitivity analysis of the i* optimisation model |
| url | http://hdl.handle.net/20.500.11937/14410 |