Bi-Level Optimization Model for Transportation Infrastructure Restoration
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Solution Overview
Problem
Current methods for restoring transportation infrastructure after disruptive events are inefficient and costly, as they fail to effectively consider unmet demand in transportation systems, leading to biased restoration results and significant material and human costs.
Innovation Solution
A bi-level optimization model is introduced that combines travel time and unmet demand to measure transportation system resilience, using Elastic User Equilibrium (EUE) to select road sections for restoration and allocate resources, with the upper level problem optimizing road section selection and resource allocation, and the lower level problem modeling traveler behavior and network-flow assignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional restoration methods are used that focus only on travel time, then travel time may be reduced, but unmet demand is not considered leading to biased restoration results
Solution Approach 1:
The patent changes the parameters used to evaluate restoration plans by introducing a comprehensive resilience measure that combines both travel time and unmet demand. This dual-parameter approach transforms the single-dimensional evaluation (travel time only) into a multi-dimensional evaluation system, allowing for more balanced and reliable restoration decisions that consider both efficiency and service coverage.
2Reliability
If more road sections are restored, then system resilience improves, but material and human costs increase
Solution Approach 1:
The patent transforms the restoration optimization problem by changing the objective function parameters to include both resilience improvement and cost considerations. The bi-level optimization model uses resilience measure (combining travel time and unmet demand) as the upper-level objective while incorporating cost constraints, enabling decision-makers to achieve the best resilience improvement within limited budgetary and resource constraints.
3Quantity of substance
If limited budget is constrained, then resource allocation must be optimized, but restoration effectiveness may be reduced
Solution Approach 1:
The patent addresses budget constraints by transforming the restoration planning into a bi-level optimization problem where the upper level maximizes resilience measure subject to budget constraints, and the lower level models traveler behavior. This parameter transformation allows for optimal allocation of limited resources to achieve maximum restoration effectiveness within the given budget, rather than simply reducing restoration scope.
Data Source
AI summary
A system and method for transportation infrastructure restoration, assuming limited budget constraints and considering unmet demand in the system for maximizing transportation system resilience is provided.