A parametric approach to integer linear fractional programming: Newton’s and Hybrid-Newton methods for an optimal road maintenance problem

Park, Chong Hyun; Lim, Heejong

doi:10.1016/j.ejor.2019.07.010

Cited by 8 publications

(5 citation statements)

References 32 publications

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“…Moreover, optimisation can promote the best use of available resources, deal with uncertainties and different management outcomes, examine their trade-offs and involve multiple objectives. The most common optimisation tools employed for infrastructure maintenance, rehabilitation or renewal project selection are linear programming (Grivas et al, 1993;Abiri-Jahromi et al, 2009;Park and Lim, 2021) and heuristic methods , for instance, genetic algorithms (Miyamoto et al, 2000;Tack and Chou, 2002;Juan et al, 2010). Multi-criteria decision-aiding tools have also been used for decision tools for asset management (Kiss and Tanczos, 1998;Bana e Costa et al, 2006;Fiorencio et al, 2015) as well as data envelopment analysis (Rogers and Louis, 2007;Tavana et al, 2015) In general, asset project selection problems can be classified into two types: budget allocation and budget planning.…”

Section: Decision Models For Project Selection In Asset Managementmentioning

confidence: 99%

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

Vilarinho,

Barbosa,

Nóvoa

et al. 2023

Int Trans Operational Res

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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.

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Section: Decision Models For Project Selection In Asset Managementmentioning

confidence: 99%

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

Vilarinho,

Barbosa,

Nóvoa

et al. 2023

Int Trans Operational Res

View full text Add to dashboard Cite

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“…Khiavi and Mohammadi traded off the agency cost, the user cost, and the road residual value with NSGA II, and obtained optimal weights of the M&R outcomes for a pavement network in Texas [41]. Other studies also successfully used MOO to generate and trade off the best M&R outcomes, and reached a compromised M&R decision [42][43][44]. This methodology can also be used to determine the appropriate annual budgets when making M&R decisions.…”

Section: Plos Onementioning

confidence: 99%

Network-level pavement maintenance and rehabilitation decision-making with the optimized annual budget

Chen

2023

PLoS ONE

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Maintenance and rehabilitation (M&R) is necessary to keep pavement networks in good condition. Due to the capital intensity, M&R funding is always insufficient. The annual budget, determining the available funding, is a critical criterion when planning M&R treatments. However, its values are often given, and the determination of the values is seldom discussed. To fill the gap, this paper focuses on both the determination of annual budgets and the budget allocations, and therefore enhances the network-level decision-making on M&R by developing a Multi-Objective Optimization (MOO) method. This method does not only optimize and trade off the annual budgets and their consequences, but also allocates the funding across the entire network through generating the optimized M&R decisions. According to a case study with 50 segments, the developed method successfully and effectively identified non-linear discrete relationship between the minimized annual budgets and the maximized M&R benefits subject to all the constraints, and generated the optimized annual budget allocation for each M&R decision. The achievements of this paper can be used to enhance the efficiency of M&R decisions and contribute to informed pavement management.

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“…The quality of buildings and their facilities is often poor because of a lack of proper building maintenance and management, even with high maintenance costs [34][35][36]. In addition, once passive management is adopted, various types of building defects, including structural or nonstructural cracking and concrete fragments spalling, can cause severe damage.…”

Section: Maintenancementioning

confidence: 99%

Integrated Building Maintenance and Safety Framework: Educational and Public Facilities Case Study

et al. 2022

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The facility safety is a highly important issue in educational institutions and public facilities, where the safety and health of the occupants (students, educational and public service staff) is a high-order priority. The research hypothesizes that a synergy exists between the maintenance and safety of public facilities. Analytical–empirical research methods were aimed at the development of an integrated maintenance–safety framework. The framework was validated through inferential statistics and a case study. A correlation (R2) of 0.74 between the level of maintenance and the safety level of 24 educational facilities was found using the Pearson correlation coefficient. The levels of maintenance and of safety observed were marginal. An innovative Integrated Safety–maintenance performance framework was developed for synergetic safety–maintenance monitoring, control and management. The framework proposes a cycle loop of safety–maintenance–performance audits of facilities as a key tool for advanced maintenance and safety management in public facilities. The framework was validated in a case study of public facility. The time history of maintenance performance and safety shows a high level of fitness (R2 = 0.8865, p-Value < 0.05). These research findings stress that integrated safety and maintenance should be implemented as a unified procedure to enhance the advanced maintenance performance and safety climate in public facilities management.

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A parametric approach to integer linear fractional programming: Newton’s and Hybrid-Newton methods for an optimal road maintenance problem

Cited by 8 publications

References 32 publications

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

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

Network-level pavement maintenance and rehabilitation decision-making with the optimized annual budget

Integrated Building Maintenance and Safety Framework: Educational and Public Facilities Case Study

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