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An ant colony system-based hybrid algorithm for an emergency roadway repair time-space network flow problem

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Facility Location and Emergency Management Metaheuristic Optimization Algorithms Research Vehicle Routing Optimization Methods

Abstract

In this study, we employ an ant colony system (ACS) algorithm, coupled with a threshold accepting technique, to develop an ACS-based hybrid algorithm that is capable of efficiently solving an emergency roadway repair time-space network flow problem. To test how well the algorithm may be applied to actual operations, we perform a case study using data from the 1999 Chi-Chi earthquake in Taiwan. To assess the robustness of the model and solution algorithm for different roadway network patterns, we generate 16 problem instances with four different roadway network patterns. The method that uses CPLEX to directly solve the problem and a previously proposed heuristic are used to compare with our algorithm. The test results show that our algorithm is both effective and efficient enough to solve problems with different roadway networks, and therefore, would be useful in practice.

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References

2000Optimized resource allocation for emergency response after earthquake disasters 2008Optimal scheduling of emergency roadway repair and subsequent relief distribution 2007A time‐space network model for work team scheduling after a major disaster 2009Inter-city bus scheduling for allied carriers

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2014Optimal Scheduling for Highway Emergency Repairs Under Large-Scale Supply–Demand Perturbations 2022Trends and gaps in the literature of road network repair and restoration in the context of disaster response operations 2021Synchronizing victim evacuation and debris removal: A data-driven robust prediction approach 2020Robust post-disaster route restoration 2015Emergency scheduling of engineering rescue tasks in disaster relief operations and its application in China 2017Emergency materials transportation model in disasters based on dynamic programming and ant colony optimization

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