Identification of vulnerable transportation infrastructure and household decision making under emergency evacuation conditions

This report combines two primary problems under general disaster considerations. First, a methodology is presented to identify vulnerable transportation infrastructure, which is defined as the set of network links, the damage of which results in the maximum disruption of the network's origin-destination connectivity. The disrupting agent is permitted a limited number of resources with which to damage the network. The measure of disruption, resulting from the damage, is based on a given set of traffic conditions, the availability of alternate paths, and roadway design characteristics. A bi-level mathematical programming model represents the interaction of the traffic assignment and the disruption measure. This bi-level model allows the problem to be viewed as a game between an evil entity, who seeks to disrupt the network, and a traffic management agency that routes vehicles so as to avoid vulnerable links to the greatest degree possible while meeting origin-destination demands. The second problem is to mathematically describe household decision making behavior in an emergency evacuation. Traditional transportation network evacuation models have omitted a commonly observed sociological phenomenon - that families gather together before evacuating an area. This omission can lead to overly optimistic evacuation times, and the evacuation models fail to capture underlying traffic patterns that only arise during times of crises. Two linear integer programs are developed to model the decision making behavior; the first describes a meeting location selection process and the second assigns trip chains for drivers to pick up family members who may not have access to a vehicle. The mathematical programs are combined with a traffic assignment-simulation package for evacuation analysis. Interactions between the two problems are also explored. Evacuation conditions are examined when the traffic management agency routes traffic around vulnerable links. The impact of the unusual traffic patterns, that arise using the household decision making behavior evacuation model, is evaluated in terms of shifts in the relative vulnerability of the transportation links. Finally, the routing strategies are evaluated for extensions in network evacuation times.

[1]  J. Harsanyi Cardinal Welfare, Individualistic Ethics, and Interpersonal Comparisons of Utility , 1955 .

[2]  David Valinsky Symposium on Applications of Operations Research to Urban Services—A Determination of the Optimum Location of Fire-Fighting Units in New York City , 1955 .

[3]  Charles E. Fritz,et al.  The Rio Grande Flood: A Comparative Study of Border Communities in Disaster.@@@An Introduction to Methodological Problems of Field Studies in Disasters.@@@Convergence Behavior in Disasters: A Problem in Social Control. , 1958 .

[4]  R. Luce,et al.  Individual Choice Behavior: A Theoretical Analysis. , 1960 .

[5]  G. Clarke,et al.  Scheduling of Vehicles from a Central Depot to a Number of Delivery Points , 1964 .

[6]  A. Rapoport,et al.  Two-Person Game Theory: The Essential Ideas. , 1967 .

[7]  Brian W. Kernighan,et al.  An Effective Heuristic Algorithm for the Traveling-Salesman Problem , 1973, Oper. Res..

[8]  Benjamin F McLuckie,et al.  Centralization and Natural Disaster Response - Preliminary Hypothesis and Interpretations , 1975 .

[9]  Ronald W. Perry,et al.  Integrated Systems and Emergent Norm Approach to Mass Emergencies , 1976 .

[10]  Robert A. Russell,et al.  Technical Note - An Effective Heuristic for the M-Tour Traveling Salesman Problem with Some Side Conditions , 1977, Oper. Res..

[11]  Social decision making in the presence of complex goals, ethics and the environment , 1979 .

[12]  R. Duncan Luce,et al.  Individual Choice Behavior: A Theoretical Analysis , 1979 .

[13]  S.H. Lee,et al.  Reliability Evaluation of a Flow Network , 1980, IEEE Transactions on Reliability.

[14]  Horace W. Brock,et al.  The Problem of "Utility Weights" in Group Preference Aggregation , 1980, Oper. Res..

[15]  H. W. Corley,et al.  Most vital links and nodes in weighted networks , 1982, Oper. Res. Lett..

[16]  Warren B. Powell,et al.  A transportation network evacuation model , 1982 .

[17]  The Counterfeit Ark: Crisis Relocation for Nuclear War , 1984 .

[18]  Ronald W. Perry,et al.  Disaster Management: Warning Response and Community Relocation , 1984 .

[19]  R. Ballou DISPLAN: A multiproduct plant/warehouse location model with nonlinear inventory costs , 1984 .

[20]  Gilbert Laporte,et al.  Two exact algorithms for the distance-constrained vehicle routing problem , 1984, Networks.

[21]  J. Smith,et al.  A k-SHORTEST PATHS ROUTING HEURISTIC FOR STOCHASTIC NETWORK EVACUATION MODELS , 1984 .

[22]  David J. Eaton,et al.  Determining Emergency Medical Service Vehicle Deployment in Austin, Texas , 1985 .

[23]  Moshe Ben-Akiva,et al.  Discrete Choice Analysis: Theory and Application to Travel Demand , 1985 .

[24]  Y. She Urban Transportation Networks: Equilibrium Analysis with Mathematical Programming Methods , 1985 .

[25]  K. K. Aggarwal,et al.  Integration of Reliability and Capacity in Performance Measure of a Telecommunication Network , 1985, IEEE Transactions on Reliability.

[26]  Bruce L. Golden,et al.  Vehicle Routing with Time-Window Constraints , 1986 .

[27]  Edward K. Baker,et al.  Solution Improvement Heuristics for the Vehicle Routing and Scheduling Problem with Time Window Constraints , 1986 .

[28]  Alexander H. G. Rinnooy Kan,et al.  Vehicle Routing with Time Windows , 1987, Oper. Res..

[29]  Marius M. Solomon,et al.  Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints , 1987, Oper. Res..

[30]  Mwp Martin Savelsbergh,et al.  VEHICLE ROUTING WITH TIME WINDOWS: OPTIMIZATION AND APPROXIMATION. VEHICLE ROUTING: METHOD AND STUDIES. STUDIES IN MANAGEMENT SCIENCE AND SYSTEMS - VOLUME 16 , 1987 .

[31]  A Assad,et al.  VEHICLE ROUTING WITH SITE DEPENDENCIES. VEHICLE ROUTING: METHODS AND STUDIES. STUDIES IN MANAGEMENT SCIENCE AND SYSTEMS - VOLUME 16 , 1988 .

[32]  Steven J. Brams,et al.  Game Theory and National Security , 1988 .

[33]  Siamak Ardekani,et al.  Logistics problems in the aftermath of the 1985 Mexico City earthquake , 1988 .

[34]  Rajan Batta,et al.  Optimal Obnoxious Paths on a Network: Transportation of Hazardous Materials , 1988, Oper. Res..

[35]  Hasan Pirkul,et al.  The siting of emergency service facilities with workload capacities and backup service , 1988 .

[36]  M M Solomon,et al.  VEHICLE ROUTING AND SCHEDULING PROBLEMS WITH TIME WINDOW CONSTRAINTS: EFFICIENT IMPLEMENTATIONS OF SOLUTION IMPROVEMENT PROCEDURES , 1988 .

[37]  Eliahu Stern,et al.  A behavioural-based simulation model for urban evacuation , 1989 .

[38]  Y Iida,et al.  AN APPROXIMATION METHOD OF TERMINAL RELIABILITY OF ROAD NETWORK USING PARTIAL MINIMAL PATH AND CUT SETS , 1989 .

[39]  Erhan Erkut,et al.  Analytical models for locating undesirable facilities , 1989 .

[40]  Hani S. Mahmassani,et al.  GUIDELINES AND COMPUTATIONAL RESULTS FOR VECTOR PROCESSING OF NETWORK ASSIGNMENT CODES ON SUPERCOMPUTERS , 1989 .

[41]  R. Vohra,et al.  Finding the most vital arcs in a network , 1989 .

[42]  M. Brandeau,et al.  An overview of representative problems in location research , 1989 .

[43]  David Simchi-Levi,et al.  Optimal locations and districts of two traveling salesmen on a tree , 1990, Networks.

[44]  S Rattien The role of the media in hazard mitigation and disaster management. , 1990, Disasters.

[45]  L S Walter,et al.  The uses of satellite technology in disaster management. , 1990, Disasters.

[46]  A. K. Mittal,et al.  The k most vital arcs in the shortest path problem , 1990 .

[47]  Rajan Batta,et al.  Covering-Location Models for Emergency Situations That Require Multiple Response Units , 1990 .

[48]  Charles J. Colbourn,et al.  Combining monte carlo estimates and bounds for network reliability , 1990, Networks.

[49]  David T. Herbert,et al.  The Emergency Evacuation of Cities: A Cross-National Historical and Geographical Study , 1991 .

[50]  Thomas M. Kisko,et al.  Regional Evacuation Modeling System (REMS): A decision support system for emergency area evacuations , 1991 .

[51]  Ronald W. Perry,et al.  Behavioral foundations of community emergency planning , 1992 .

[52]  Eliahu Stern,et al.  Simulating the evacuation of a small city: the effects of traffic factors , 1993 .

[53]  H. Raiffa,et al.  Decisions with Multiple Objectives , 1993 .

[54]  L. V. Wassenhove,et al.  Interactions between operational research and environmental management , 1995 .

[55]  Nien-Sheng Hsu,et al.  Water Distribution Network Reliability: Connectivity Analysis , 1996 .

[56]  Vladimir Marianov,et al.  The Queueing Maximal availability location problem: A model for the siting of emergency vehicles , 1996 .

[57]  Eduardo Conde,et al.  Semi-obnoxious location models: A global optimization approach , 1997 .

[58]  Christos Douligeris,et al.  Optimal location and capacity of emergency cleanup equipment for oil spill response , 1997 .

[59]  Said Salhi,et al.  The obnoxious p facility network location problem with facility interaction , 1997 .

[60]  John N. Tsitsiklis,et al.  Introduction to linear optimization , 1997, Athena scientific optimization and computation series.

[61]  Jonathan F. Bard,et al.  Two-Level Mathematical Programming Problem , 1997 .

[62]  C. Simkin. About Economic Inequality , 1998 .

[63]  Marvin B. Mandell,et al.  Covering models for two-tiered emergency medical services systems , 1998 .

[64]  Hani S. Mahmassani,et al.  DEFINING SPECIAL-USE LANES , 1999 .

[65]  Yasuo Asakura Evaluation of network reliability using stochastic user equilibrium , 1999 .

[66]  Emanuel Melachrinoudis,et al.  Bicriteria location of a semi-obnoxious facility , 1999 .

[67]  Hong Kam Lo,et al.  A capacity related reliability for transportation networks , 1999 .

[68]  José Muñoz-Pérez,et al.  Location of an undesirable facility in a polygonal region with forbidden zones , 1999, Eur. J. Oper. Res..

[69]  Frank Plastria,et al.  Undesirable facility location with minimal covering objectives , 1999, Eur. J. Oper. Res..

[70]  Yasunori Iida,et al.  BASIC CONCEPTS AND FUTURE DIRECTIONS OF ROAD NETWORK RELIABILITY ANALYSIS , 1999 .

[71]  Michael G.H. Bell Measuring network reliability: A game theoretic approach , 1999 .

[72]  Michael G.H. Bell,et al.  A game theory approach to measuring the performance reliability of transport networks , 2000 .

[73]  Blas Pelegrín,et al.  A continuous location model for siting a non-noxious undesirable facility within a geographical region , 2000, Eur. J. Oper. Res..

[74]  Hani S. Mahmassani,et al.  Dynamic Traffic Assignment in Design and Evaluation of High-Occupancy Toll Lanes , 2000 .

[75]  Christopher Cassir The n+m person game approach to network reliability , 2000 .

[76]  Der-Horng Lee,et al.  Accelerating Strategies and Computational Studies of the Frank–Wolfe Algorithm for the Traffic Assignment Problem , 2001 .

[77]  T Plowman,et al.  DANGER! HURRICANE COMING , 2001 .

[78]  Hani S. Mahmassani,et al.  Methodology for Assessing High-Occupancy Toll-Lane Usage and Network Performance , 2001 .

[79]  Susan L. Cutter,et al.  Emerging Hurricane Evacuation Issues: Hurricane Floyd and South Carolina , 2002 .

[80]  Pamela Murray-Tuite,et al.  Model of Household Trip-Chain Sequencing in Emergency Evacuation , 2003 .

[81]  H. Jaap van den Herik,et al.  Games, Theory and Applications , 2004, SOFSEM.