This paper presents a semantic framework for supporting the cost–benefit analysis in urban transit rehabilitation decisions. The use of semantic representations of decision parameters allows for more effective knowledge management practice and easier accumulation and access of corporate knowledge regarding balancing traditional construction investments with the costs to the environment, local business, and impacts on traffic. A sample illustrative case was considered by this study. It includes a comparison of a hypothetical scenario of building a monorail to replace an existing streetcar in one of Toronto's most congested streets: King Street. A microscopic simulation model for the King Street route has been developed and used in comparing the status quo to the proposed scenario in terms of impacts on traffic performance. A cost–benefit analysis has been conducted to assess the feasibility of both options. The study investigated direct costs such as monorail construction cost, streetcar system removal cost, and operating and maintenance costs of both systems. The sustainability-related costs included user costs and accident costs.Key words: sustainable infrastructure, knowledge management, cost–benefit analysis.
Fuzzy-Monte Carlo Simulation for Cost Benefit Analysis of Knowledge Management System Investment
