{"type":"ScholarlyArticle","title":"Simulation-Assisted Optimization for Large-Scale Evacuation Planning with Congestion-Dependent Delays","authors":[{"name":"Kazi Ashik Islam","slug":"kazi-ashik-islam","given":"Kazi Ashik","family":"Islam","affiliation":"Biocomplexity Institute , University of Virginia {ki5hd , wny7gj ,"},{"name":"Da Qi Chen","slug":"da-qi-chen","given":"Da Qi","family":"Chen","affiliation":"Biocomplexity Institute , University of Virginia {ki5hd , wny7gj ,"},{"name":"Madhav Marathe","slug":"madhav-marathe","given":"Madhav","family":"Marathe","affiliation":"Biocomplexity Institute , University of Virginia {ki5hd , wny7gj ,"},{"name":"Henning Mortveit","slug":"henning-mortveit","given":"Henning","family":"Mortveit","affiliation":"Biocomplexity Institute , University of Virginia {ki5hd , wny7gj ,"},{"name":"Samarth Swarup","slug":"samarth-swarup","given":"Samarth","family":"Swarup","affiliation":"Biocomplexity Institute , University of Virginia {ki5hd , wny7gj ,"},{"name":"Anil Vullikanti","slug":"anil-vullikanti","given":"Anil","family":"Vullikanti","affiliation":"Biocomplexity Institute , University of Virginia {ki5hd , wny7gj ,"}],"abstract":"Evacuation planning is a crucial part of disaster management. However, joint optimization of its two essential components, routing and scheduling, with objectives such as minimizing average evacuation time or evacuation completion time, is a computationally hard problem. To approach it, we present MIP-LNS, a scalable optimization method that utilizes heuristic search with mathematical optimization and can optimize a variety of objective functions. We also present the method MIP-LNS-SIM, where we combine agent-based simulation with MIP-LNS to estimate delays due to congestion, as well as, find optimized plans considering such delays. We use Harris County in Houston, Texas, as our study area. We show that, within a given time limit, MIP-LNS finds better solutions than existing methods in terms of three different metrics. However, when congestion dependent delay is considered, MIP-LNS-SIM outperforms MIP-LNS in multiple performance metrics. In addition, MIP-LNS-SIM has a significantly lower percent error in estimated evacuation completion time compared to MIP-LNS.","doi":"10.24963/ijcai.2023/595","url":"https://ijcai.org/proceedings/2023/595","pdf":"https://ijcai.org/proceedings/2023/0595.pdf","markdown":"https://ijcai.org/proceedings/2023/595.md","bibtex":"https://ijcai.org/proceedings/2023/bibtex/595","volume":{"slug":"2023","title":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2023","url":"https://ijcai.org/proceedings/2023/","year":2023,"location":"Macao, SAR","dates":"19-25 August 2023","editors":"Edith Elkind","isbn":"978-1-956792-03-4","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2023"},"section":"Planning and Scheduling","track":"Main Track","number":595,"pages":{"first":5359,"last":5367},"keywords":["Agent-based and Multi-agent Systems: MAS: Applications","Constraint Satisfaction and Optimization: CSO: Constraint optimization","Planning and Scheduling: PS: Search in planning and scheduling","Search: S: Heuristic search"],"videos":[],"references":[{"position":1,"raw":"[Adiga et al., 2015] Abhijin Adiga, Aditya Agashe, Shaikh Arifuzzaman, Christopher L. 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