Abusamra, Soliman (2018) Coordination and Multi-Objective Optimization Framework for Managing Municipal Infrastructure Under Performance-Based Contracts. PhD thesis, Concordia University.
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Abstract
One-third of Canada’s municipal infrastructure is in fair, poor and failing condition states. Aging infrastructure systems are placing tremendous pressure on governments through steeply growing budget deficits and an urgent need for replacement. Municipalities are experiencing high inefficiency and financial burden imposed by their under-performing infrastructure, which in return increases the risk of service disruption and leaves decision-makers with no choice but undertake immediate interventions. The estimate of Canada’s infrastructure deficit is ranging between $110 billion to $270 billion. The massive number of infrastructure intervention activities occurring in cities leads to detrimental social, environmental, and economic impacts on the community. Thus, coordinating the interventions of the co-located assets (i.e. roads, water, and sewer) is progressively becoming of importance to cope with those tough challenges. It will decrease the number of service disruptions and reduce the rehabilitation costs by integrating the joint activities shared among the co-located assets. Numerous attempts have been made by previous scholars to enhance the infrastructure performance within the limited budgets. Yet, most of their efforts were geared towards short-term intervention planning for a single asset, without accounting for the potential coordination savings (i.e. cost, disruption time, consumed space, amount of service disruption, and end users’ inconvenience).
In the lights of those issues, this research proposes a coordination and multi-objective optimization framework for managing the municipal infrastructure under performance-based contracts. The framework proposes an integrated contractual and asset management solution to aid decision-makers in both the pre-contract and post-contract phases. In the pre-contract phase, the system will find a near-optimal set of key performance indicators thresholds’ as well as their associated penalties and incentives that meet the end users’ expectations without having an escalated contingency at the contractual price. In the post-contract phase, it will provide a near-optimum coordinated interventions’ schedule/plan for the municipal infrastructure. To build the framework, the research went through three main phases: (1) literature review that thoroughly studied and analyzed the municipal contractual practices, optimization, and integrated asset management; (2) contractual scheme, coordination, and multi-objective optimization asset management system where a novel contractual scheme was introduced and a coordination and optimization-based asset management system was developed; and (3) system integration and model implementation where the contractual scheme was integrated with the coordination and optimization-based asset management system to aid decision-makers in taking informed pre-contract and post-contract decisions. The coordination and optimization systems were built to quantify and evaluate the potential savings of coordinating the maintenance, whether partially or fully, as opposed to the conventional approach. It revolves through three core models: (1) central database that contains detailed asset inventory for the infrastructure systems, (2) multi-dimensional performance assessment computational models that assess the potential coordination savings for the three coordination scenarios based on eight indicators (time, space, cost, risk, resilience preparedness, condition, efficiency, and effectiveness); and (3) two multi-objective optimization models: (a) multi-objective hierarchical goal optimization that relies on a set of meta-heuristic rules and genetic algorithms optimization engine; (b) multi-objective linear programming optimization that reaches an exact solution using MOSEK software.
To demonstrate the system’s functionality, it was applied to the roads’, water and sewer networks of two case studies namely: (1) city of Montreal; and (2) town of Kindersley. Both displayed huge savings in favor of the coordinated approach as opposed to the conventional one. For the city of Montreal, the system was developed on sophisticated spreadsheets combined with a genetic algorithms’-based optimization engine (Evolver) and was applied to both pre-contract and post-contract phases. The pre-contract optimization was able to obtain a near-optimal set of key performance indicators’ thresholds and their associated penalties and incentives. The post-contract optimization displayed an overall improvement of 15% across 25 years planning horizon as a result of coordinating the interventions as opposed to the conventional scenario. The 15% improvement was broken down to 12%, 16%, 18%, 30%, 26%, 10%, 10% for the time, space, cost, efficiency, effectiveness, condition, and risk respectively. For the town of Kindersley, the system was developed on REMSOFT software integrated with MOSEK optimization engine. The results displayed an overall improvement of 29% across 25 years planning horizon because of coordinating the interventions as opposed to conventional ones. The 29% improvement was broken down to 72%, 63%, 48%, 67%, 9%, 1%, 14%, and 5% for the time, space, cost, efficiency, effectiveness, condition, resilience preparedness and risk respectively. Furthermore, the coordinated intervention program resulted in 67% fewer interventions as opposed to the conventional approach, saving an overall of 374 interventions across the 25 years, equivalent to 15 interventions annually, which drastically reduces the public disruption. In conclusion, this research proposes an integrated coordination, optimization, and contractual solution for the municipalities and maintenance contractors to enhance their expenditures’ utilization, minimize the service disruptions, and improve their assets’ performance under tough budgetary constraints.
| Divisions: | Concordia University > Gina Cody School of Engineering and Computer Science > Building, Civil and Environmental Engineering |
|---|---|
| Item Type: | Thesis (PhD) |
| Authors: | Abusamra, Soliman |
| Institution: | Concordia University |
| Degree Name: | Ph. D. |
| Program: | Civil Engineering |
| Date: | 26 November 2018 |
| Thesis Supervisor(s): | Amador, Luis and Zayed, Tarek |
| Keywords: | Asset Management; decision-making; maintneance planning; stategic level management; coordination; roads; water; sewer; municipal infrastructure; performance-based contracts; optimization; multi-objective; life-cycle costing; deterioration; key performance indicators; goal programming |
| ID Code: | 985084 |
| Deposited By: | Soliman Abusamra |
| Deposited On: | 10 Jun 2019 12:58 |
| Last Modified: | 21 Mar 2021 01:00 |
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