A Coordination and Optimization Approach for Managing Urban Infrastructure: Coordinated Asset Management and Optimzaiton Framework For Urban Infrasructure

Dr. Soliman Amr Abu-Samra

ISBN 10: 1093492635 / ISBN 13: 9781093492637

Published by Independently published, 2019

About this Item

336 pages. 11.69x8.27x0.84 inches. In Stock.

Seller Inventory # zk1093492635

Bibliographic Details

• Title: A Coordination and Optimization Approach for Managing Urban Infrastructure: Coordinated Asset Management and Optimzaiton Framework For Urban Infrasructure
• Publisher: Independently published
• Publication Date: 2019
• Language: English
• ISBN 10: 1093492635
• ISBN 13: 9781093492637
• Binding: Paperback
• Condition: Brand New
• Weight: 1 kilogram

About this title

Synopsis

Infrastructure is at risk. Governments are challenged with growing deficits; deteriorating infrastructure; limited financial resources; and increasing levels of service expectations. 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 gradually becoming an appealing mechanism to cope with those tough challenges and efficiently repair the assets. This book introduces a novel contractual scheme to involve the private sector in the process. Furthermore, it presents a coordination and optimization approach for proactively managing a cities' infrastructure. The system is designed to analyze the potential coordination benefits in terms of time, space and costsavings; condition and risk improvement; resilience preparedness; and efficiency and effectiveness gains. Weibull and multivariate regression deterioration models are developed for representing the assets’ deterioration. A novel tri-level goal optimization approach was developed to trade-off various alternatives and select the optimum intervention plan. The system was modelled on different platforms using both evolutionary and linear-programming-based optimization engines. Furthermore, it was applied to two case studies in Canada; namely, the city of Montreal and the town of Kindersley.