Optimisation models for project selection in asset management: an application to the water sector

• Published in: International transactions in operational research 2024-09, Vol.31 (5), p.2956-2987
• Main Authors: Vilarinho, Hermilio, Barbosa, Flávia, Nóvoa, Henriqueta, Silva, Jaime Gabriel, Yamada, Luciana, Camanho, Ana S.
• Format: Article
• Language: English
• Subjects: Asset management; Business metrics; capital investment planning; Capital investments; Decision making; Evolutionary algorithms; Genetic algorithms; Integer programming; Linear programming; Mixed integer; mixed‐integer linear programming; multi‐objective programming; Optimization models; performance indicator; Portfolio investments; Project management; project selection; Pumping stations; Water supply systems
• ISSN: 0969-6016; 1475-3995
• DOI: 10.1111/itor.13365

A significant challenge in asset management is the selection of investment projects for infrastructures, which often relies on subjective judgement and lacks structured decision support methods. This challenge is particularly complex in water systems due to the diverse and heterogeneous nature of the components requiring investment. While the infrastructure value index (IVI) is widely used to characterise assets and support investment decisions in the water sector, its application in optimisation models for generating efficient project portfolios remains unexplored. To address this research gap, this study introduces optimisation models for generating investment portfolio plans in water systems' asset management. The proposed approach includes two mixed‐integer linear programming (MILP) models that determine optimal solutions and an evolutionary algorithm that offers sub‐optimal alternative investment selection plans to provide decision‐makers with additional choices for balancing optimal outcomes. The primary contribution of this research is the combined utilisation of MILP and evolutionary algorithms, integrating the IVI into the decision‐making process. These tools provide decision‐makers with structured methods for defining investment plans and minimising the subjective elements typically associated with such processes. To illustrate the effectiveness of the models, a case study is presented involving a pumping station of a Portuguese water company. The results demonstrate the practical application and benefits of the proposed approach in optimising investment decisions. This research contributes to advancing asset management practices by integrating quantitative optimisation techniques and leveraging the IVI, thereby enhancing the objectivity and efficiency of investment planning in water systems' asset management.