Value-focused modelling to generate alternatives -- Coupling multi-criteria decision analysis and optimisation models to support strategic decisions

2026-05-22

AI Summary

This study addresses the limitations of conventional energy system models, which often generate alternatives that overlook stakeholder concerns, and traditional multi-criteria decision analysis (MCDA), which relies on predefined options and inadequately explores the feasible solution space. To overcome these issues, the authors propose a value-focused alternative generation method (VF-MGA) that, for the first time, bidirectionally couples MCDA with modeling to generate alternatives (MGA). This approach embeds stakeholder values directly into the optimization process, automatically producing a diverse set of technically feasible and value-aligned alternatives. Preference-based evaluation of these alternatives supports strategic decision-making. Demonstrated in a university campus decarbonization case study, VF-MGA generated 691 relevant alternatives, effectively identifying preferred solutions and refining preference information, thereby validating its generality and practical utility.

Abstract

Decision support methods from operations research are widely used to support complex planning decisions. Within the energy sector, energy system models (ESMs) applying modelling to generate alternatives (MGA) generate large sets of near-optimal, different system configurations. However, they typically generate and analyse alternatives in the model variable space without ensuring stakeholder relevance. Multi-criteria decision analysis (MCDA), in contrast, provides a structured means to account for conflicting objectives and heterogeneous stakeholder interests but often relies on a limited set of pre-defined alternatives that may not appropriately represent the feasible solution space. To address these limitations, this work proposes value-focused modelling to generate alternatives (VF-MGA), a novel methodology that bidirectionally couples MGA and MCDA. Stakeholder objectives elicited within the MCDA inform the MGA-algorithm, enabling a stakeholder-orientated diversification of the alternatives, which are subsequently evaluated within the MCDA based on elicited stakeholder preferences, thereby providing a comprehensive decision basis. Applied to a case study on the decarbonised energy supply of a large university campus, involving eleven stakeholders representing diverse institutional groups, VF-MGA (i) systematically integrates stakeholder objectives into the generation of 691 alternatives reflecting stakeholder-relevant interests, (ii) enables the identification of stakeholder-relevant alternatives from this large set through MCDA-based evaluation, and (iii) provides more differentiated stakeholder preference information by evaluating a large and diverse set of alternatives, thereby revealing acceptable ranges for system options. With this, VF-MGA provides a generalisable methodology for complex planning decision integrating quantitative modelling with participatory decision analysis.

Problem

• energy system models
• modelling to generate alternatives
• multi-criteria decision analysis
• stakeholder preferences
• strategic decision support

Innovation

• value-focused modelling
• modelling to generate alternatives
• multi-criteria decision analysis
• stakeholder integration
• energy system optimization