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Asset Levels of Service-based Decision Support System for Municipal Infrastructure Investment

  • Author / Creator
    Sharma, Vishal
  • The single biggest challenge facing municipalities today is a shortage of funds and labor for upgrading and expanding aging infrastructure. This continued lack of funding impairs the municipalities’ ability to maintain desired levels of service. Over the last decade, many Canadian municipalities have faced pressures of increasing complexity in infrastructure asset management decision-making which can be partly attributed to cost escalation, increasing service demand and interdependencies between networks. The goal of this research is to develop the framework for Asset Levels of Service (ALOS)-based decision support systems for municipal infrastructure network investment. The proposed framework is based on the fact that ALOS should be one of the main criteria for municipal infrastructure maintenance, repair and rehabilitation (MR&R). Since ALOS is based on qualitative and quantitative parameters, the use of ALOS in municipal infrastructure MR&R decisions will result in improved funding allocation. Secondary parameters used for municipal infrastructure investment decision making in the proposed framework are the physical deterioration of assets, future growth and the impact on the dependent infrastructure network. The proposed framework focuses on funding allocation for the MR&R of municipal networks. The framework is applicable to municipal infrastructure networks, excluding the other assets such as buildings, parks, etc. Application of the proposed framework is demonstrated by its implementation in the case of urban roads. Implementation is carried out in four phases. Phase I involves the quantification of ALOS for urban roads. Quantification of ALOS for urban roads has various challenges such as multiple users and interdependencies of levels of services between various users. An Analytical Hierarchy Process (AHP) has been used to quantify ALOS. Phase II involves the determination of a multiattribute utility function for investment decision. Calculated multiattribute utility of investment decision is used in the multiobjective optimization model in Phase III. In Phase IV, the proposed methodology is incorporated into a computer application called OPTIsys (OPTImum Infrastructure SYStems). OPTIsys will facilitate MR&R decision making based on fully integrated considerations of ALOS, future demand and network interdependencies. Stakeholders benefiting from OPTIsys include the general public, asset-managers, infrastructure departments and municipal councils. OPTIsys will enable infrastructure departments to maintain the operational capability of the network in compliance with the targeted levels of service. Overall, municipalities will be able to reduce the infrastructure deficit while maximizing economic returns.

  • Subjects / Keywords
  • Graduation date
    2010-06
  • Type of Item
    Thesis
  • Degree
    Doctor of Philosophy
  • DOI
    https://doi.org/10.7939/R3XB0P
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Doctoral
  • Department
    • Department of Civil and Environmental Engineering
  • Supervisor / co-supervisor and their department(s)
    • Dr. Mohamed Al-Hussein, Department of Civil and Environmental Engineering,University of Alberta
    • Dr. Hassan Safouhi, Campus Saint Jean, University of Alberta
  • Examining committee members and their departments
    • Dr. Yasser Mohamed, Department of Civil and Environmental Engineering, University of Alberta
    • Dr. Ergun Kuru, School of Mining and Petroleum Engineering, University of Alberta
    • Dr. Tarek Hegazi (Hegazy), Department of Civil Engineering, University of Waterloo
    • Dr. Charles Robin Lindsay, Department of Economics, University of Alberta
    • Dr. Hassan Safouhi, Campus Saint Jean, University of Alberta
    • Dr. Mohamed Al-Hussein, Department of Civil and Environmental Engineering,University of Alberta