Value modelling for multi-stakeholder and multi-objective optimisation in engineering design

• Published in: Journal of engineering design Vol. 27; no. 10; pp. 697 - 724
• Main Authors: Papageorgiou, Evangelos, Eres, Murat Hakki, Scanlan, James
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 02.10.2016; Taylor & Francis Ltd
• Subjects: Analytic hierarchy process; analytic hierarchy process (AHP); Assessments; Bargaining; Decision analysis; Design engineering; Economic models; Economics; Engineering design; Game theory; Mathematical models; multi-attribute utility theory (MAUT); Multi-criteria decision analysis (MCDA); Multiple objective analysis; Nash bargaining solution (NBS); Nash equilibrium; Optimization; Stakeholders
• ISSN: 0954-4828; 1466-1837
• DOI: 10.1080/09544828.2016.1214693

The work presented culminates in the development of a value model used in the conceptual phase of engineering design, with the preferences of more than one stakeholder addressed in the multi-stakeholder and multi-objective optimisation. The 'value' of proposed solutions is assessed in an objective way from both performance and economic perspectives, while the optimal solution is identified based on the needs of the user and manufacturer, as major stakeholders. This novel value model for consistent value assessment synthesises the multi-attribute value/utility analysis with Game Theory and Analytic Hierarchy Process (AHP) assessment methodologies. During the multi-criteria decision analysis, the deficiencies, introduced by the arbitrary numerical scales used in the AHP to convert the linguistic preferences of the user between the various attributes to numerical values, are resolved. The preferences of a group of experts/decision-makers are synthesised in the group value model through the extraction of weighting factors from the individuals' AHP pairwise comparison matrices. Moreover, Game Theory is used in a hybrid cooperative/bargaining, non-cooperative non-zero sum game between the stakeholders as players, identifying the optimal design through the simultaneous employment of the Nash bargaining solution and the Nash equilibrium.