Multi-criteria optimization in bridge management
Abstract
Optimizing investment funding levels and combinations of treatment types and timings, as an aid to management decision making, are vital functions of any bridge management system (BMS). Bridge managers and engineers are finding that their constituents require bridge projects and programs to perform not only as provided by least long-term cost solutions, but also to satisfy other objectives such as safety, minimum traffic flow disruption and risk. As part of this study, a multi-criteria optimization methodology was developed not only to take due cognizance of costs but also to include a wide range of performance criteria to facilitate balanced decision-support practices in bridge management. Multi-criteria methodologies were developed for the bridge decision making problem based on the concepts of value and utility theory. Mathematical strategies were advantageously used to handle multi-dimensionality of the problem in order to capture the decision makers' preference structures effectively in a practical manner. The network level model aims to obtain the optimal selection of candidate projects from a network-wide candidate list to yield maximum network benefits subject to multiple constraints. The problem was formulated as multi-choice multi-dimensional knapsack problem. The most promising heuristics were explored and a strategy was developed that balanced theoretical precision with an appropriate level of practicality while selecting the most appropriate solution heuristic. This strategy was based on evaluating the heuristics in terms of computational speed, accuracy, robustness and simplicity. A series of computational experiments were conducted using datasets of bridge network sizes up to 50,000. The computational experiments provided very useful insights into the optimization heuristics reflecting their appropriateness and applicability to the bridge network optimization problem. IUC heuristic was found to be the most suited for large scale bridge network optimization problem with multiple criteria and multiple constraints.
Degree
Ph.D.
Advisors
Sinha, Purdue University.
Subject Area
Civil engineering
Off-Campus Purdue Users:
To access this dissertation, please log in to our
proxy server.