Multi-Objective Optimization for Bridge Management Systems (2007)

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TRANSPORTAT ION RESEARCH BOARD WASHINGTON, D.C. 2007 www.TRB.org N A T I O N A L C O O P E R A T I V E H I G H W A Y R E S E A R C H P R O G R A M NCHRP REPORT 590 Subject Areas Bridges, Other Structures, and Hydraulics and Hydrology Multi-Objective Optimization for Bridge Management Systems Vandana Patidar Samuel Labi Kumares C. Sinha School of Civil Engineering Purdue University West Lafayette, IN Paul Thompson Castle Rock, CO Research sponsored by the American Association of State Highway and Transportation Officials in cooperation with the Federal Highway Administration

NATIONAL COOPERATIVE HIGHWAY RESEARCH PROGRAM Systematic, well-designed research provides the most effective approach to the solution of many problems facing highway administrators and engineers. Often, highway problems are of local interest and can best be studied by highway departments individually or in cooperation with their state universities and others. However, the accelerating growth of highway transportation develops increasingly complex problems of wide interest to highway authorities. These problems are best studied through a coordinated program of cooperative research. In recognition of these needs, the highway administrators of the American Association of State Highway and Transportation Officials initiated in 1962 an objective national highway research program employing modern scientific techniques. 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CRP STAFF FOR NCHRP REPORT 590 Christopher W. Jenks, Director, Cooperative Research Programs Crawford F. Jencks, Deputy Director, Cooperative Research Programs David B. Beal, Senior Program Officer Eileen P. Delaney, Director of Publications Beth Hatch, Editor NCHRP PROJECT 12-67 PANEL Field of Design—Area of Bridges Richard W. Shepard, County of El Dorado, Placerville, CA (Chair) Dan Scherschligt, Kansas DOT Michael C. Brown, Virginia DOT Michel Ghosn, City College of New York George Hearn, University of Colorado–Boulder Michael B. Johnson, California DOT Omar Smadi, Iowa State University, Ames, IA Todd Thompson, South Dakota DOT Joey Hartmann, FHWA Liaison Jose L. Aldayuz, AASHTO Liaison Frank N. Lisle, TRB Liaison AUTHOR ACKNOWLEDGMENTS The project was conducted under the direction of Kumares C. Sinha, who served as the Principal Inves- tigator, with Paul D. Thompson and Samuel Labi as co-Principal Investigators. Vandana Patidar was responsible for the technical report, and Paul D. Thompson prepared the software user’s manual (which is a CD-ROM attached to this report). William A. Hyman and Arun M. Shirolé, as consultants, con- tributed to the review of the state of the practice and state of the art and the development of vulnerability performance measures. Thomas Morin, Professor of Industrial Engineering at Purdue University, is acknowledged for his assistance in the development of multiple-criteria decision-making techniques and algorithms. We also acknowledge the valuable contributions of David Beal, Richard Shepard, and the entire NCHRP 12-67 panel who participated in various surveys for the research, provided inputs for devel- oping the multi-criteria parameters, and made thoughtful comments that helped greatly to improve the quality of the research product. We are grateful to Karen Hatke and Dorothy Miller for their assistance in preparing the reports. C O O P E R A T I V E R E S E A R C H P R O G R A M S

This report describes the development of methodologies for network- and project-level optimization of multiple, user-specified performance criteria. Bridge management software modules to implement the methodologies were also developed. The report details the devel- opment of methodologies. The software modules, user’s manual, and demonstration data- base are provided on an accompanying CD-ROM. The material in this report will be of immediate interest to bridge managers and planners. Currently available bridge management system (BMS) tools compute an optimal solu- tion based on the objective of least long-term cost. Bridge managers are finding that their constituents require bridge conditions to be substantially better than a least long-term cost solution would provide. Research was needed to develop a multi-objective optimization model. To address this need, two distinct BMS optimization models were developed: a network- level model and a bridge-level model. The network-level model provides a decision- making tool that optimizes bridge actions for multiple performance criteria. These perfor- mance criteria could be cost, condition, risk, highway bridge replacement and rehabilitation (HBRR) program eligibility, bridge health index, or others. The bridge-level model evalu- ates the effect of bridge action alternatives on life-cycle cost and other performance criteria for the purpose of selecting projects that are consistent with the network goals. Both models use the AASHTO BridgeWare database supplemented with additional data as needed. Commonly Recognized (CoRe) Element data are used for condition assessments. The bridge-level model considers recommendations from the network-level model. In addi- tion, the network-level model can consider projects selected within the bridge-level model. These models also can operate independently. Both models explicitly consider the inherent uncertainties of estimated costs and outcomes. The models are implemented in graphical design software that will help bridge managers visualize the life cycle of individual bridges and bridge inventories. This research was performed by Purdue University, in West Lafayette, Indiana, and Paul D. Thompson, Consultant. The report fully documents the research leading to the recom- mended models. F O R E W O R D By David B. Beal Staff Officer Transportation Research Board

C O N T E N T S 1 Summary 5 Chapter 1 Decision-Making Context 5 1.1 Introduction 5 1.2 Characterization of Users 6 1.3 Bridge-Level Use-Cases 9 1.4 Candidates as an Interface Between Bridge and Network Levels 10 1.5 Network-Level Objectives and Constraints 10 1.6 Use-Cases at Network Level 12 1.7 Characterizing the Problem Domain 14 1.8 Dynamic View of the Problem Domain 17 1.9 Static View of the Problem Domain 19 Chapter 2 Research Approach 19 2.1 Goals and Performance Measures 19 2.2 Techniques for Multi-Criteria Decision Making 27 2.3 Network-Level Optimization—Formulation 30 2.4 Bridge-Level Optimization—Approach 36 Chapter 3 Findings and Applications 36 3.1 Developing Multi-Criteria Parameters 40 3.2 Network-Level Optimization—Solution Methods 63 3.3 Bridge-Level Optimization 86 Chapter 4 Conclusions 86 4.1 Performance Measures 86 4.2 Development of the Multi-Criteria Utility Function 87 4.3 Selection of Bridge Actions Through Optimization 87 4.4 Identification and Evaluation of Network-Level Solution Approaches 88 4.5 Application Tool (Software Package) 88 4.6 Bridge Deterioration 89 4.7 Cost Models 89 4.8 Deployment and Implementation 90 References A-1 Appendix A Review of Related Research Publications B-1 Appendix B Performance Measures Identified for This Study C-1 Appendix C Sample Questionnaire