Open AccessMULTIPLE‐CRITERIA DECISION SUPPORT SYSTEM IN HIGHWAY INFRASTRUCTURE MANAGEMENT
Author(s) -
Jana Šelih,
Anžej Kne,
Aleksander Srdić,
Marijan Žura
Publication year - 2008
Publication title -
transport
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 31
eISSN - 1648-4142
pISSN - 1648-3480
DOI - 10.3846/1648-4142.2008.23.299-305
Subject(s) - ranking (information retrieval) , asset management , risk analysis (engineering) , task (project management) , asset (computer security) , depreciation (economics) , set (abstract data type) , decision support system , process (computing) , work (physics) , driver rehabilitation , transport engineering , constraint (computer aided design) , rehabilitation , computer science , operations research , business , engineering , finance , computer security , systems engineering , artificial intelligence , economic growth , human capital , biology , operating system , machine learning , financial capital , economics , programming language , mechanical engineering , neuroscience , capital formation
Highway infrastructure represents a significant part of the public assets, and through its lifetime, is exposed to various deterioration processes leading to the depreciation of its value. It is therefore of vital importance to manage these assets aiming to reduce the loss of their value with time to a minimum. A typical task of road managers is making decisions related to maintenance, repair and rehabilitation based on data regarding the existing condition, risk of its use, life cycle costs and age. Road infrastructure is complex, and therefore the optimal choice of planned interventions is a delicate task often left to the road managers’ subjective judgment. The main goal of research work presented in the paper is the development of a multiple criteria decision support system to determine the priority ranking of asset rehabilitation projects. Results are presented for a selected case study that consists of 27 overpasses for a highway section. The data on the condition of crossovers obtained by regular inspection along their contribution to a structured database are essential. The selection of the set of asset rehabilitation projects is carried out by using the developed decision support system that includes the budget constraint option. The selected set of asset maintenance/rehabilitation projects meets best the pre‐defined combination of several criteria and therefore yields the maximized overall benefit. The results showing the selection criteria employed in the decision process and relative importance are crucial in obtaining the targeted goals. The selected criteria should therefore reflect the needs of the users and the actual conditions related to the assets.