{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T10:22:03Z","timestamp":1770718923472,"version":"3.49.0"},"publisher-location":"Cham","reference-count":32,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032163271","type":"print"},{"value":"9783032163288","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-3-032-16328-8_11","type":"book-chapter","created":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T14:37:48Z","timestamp":1770647868000},"page":"158-169","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Adjustable Attribute Matching in\u00a0Digital Similars of\u00a0Populations"],"prefix":"10.1007","author":[{"given":"Kazi Ashik","family":"Islam","sequence":"first","affiliation":[]},{"given":"S. S.","family":"Ravi","sequence":"additional","affiliation":[]},{"given":"Henning S.","family":"Mortveit","sequence":"additional","affiliation":[]},{"given":"Samarth","family":"Swarup","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,2,10]]},"reference":[{"key":"11_CR1","unstructured":"Adiga, A., et al.: Generating a synthetic population of the United States. Technical report. NDSSL 15-009, Network Dynamics and Simulation Science Laboratory (2015). https:\/\/drive.google.com\/file\/d\/1S8Z3sqCMxBGBB7WbNoPHy7ff7NtJo6GR\/view?usp=drive_link"},{"key":"11_CR2","doi-asserted-by":"publisher","unstructured":"Aleta, A., et al.: Modelling the impact of testing, contact tracing and household quarantine on second waves of COVID-19. Nat. Hum. Behaviour 4(9), 964\u2013971 (2020). https:\/\/doi.org\/10.1038\/s41562-020-0931-9","DOI":"10.1038\/s41562-020-0931-9"},{"issue":"1","key":"11_CR3","doi-asserted-by":"publisher","first-page":"28829","DOI":"10.1038\/s41598-024-79754-9","volume":"14","author":"H Anand","year":"2024","unstructured":"Anand, H., Swarup, S., Shafiee-Jood, M., Alemazkoor, N.: Understanding of income and race disparities in hurricane evacuation is contingent upon study case and design. Sci. Rep. 14(1), 28829 (2024). https:\/\/doi.org\/10.1038\/s41598-024-79754-9","journal-title":"Sci. Rep."},{"key":"11_CR4","doi-asserted-by":"crossref","unstructured":"Bhattacharya, P., et al.: Data-driven scalable pipeline using national agent-based models for real-time pandemic response and decision support. Int. J. High Performance Comput. Appl. 37(1), 4\u201327 (2023)","DOI":"10.1177\/10943420221127034"},{"key":"11_CR5","unstructured":"BuildingFootprintUSA: (2019). https:\/\/www.buildingfootprintusa.com\/, Accessed 15 Sept 2019"},{"key":"11_CR6","doi-asserted-by":"crossref","unstructured":"van Dam, K.H., Bustos-Turu, G., Shah, N.: A methodology for simulating synthetic populations for the analysis of socio-technical infrastructures. In: Jager, W., et al. (eds.) Advances in Social Simulation 2015, pp. 429\u2013434. Springer, Cham (2017)","DOI":"10.1007\/978-3-319-47253-9_39"},{"key":"11_CR7","doi-asserted-by":"crossref","unstructured":"Duan, R., Pettie, S.: Linear-time approximation for maximum weight matching. J. ACM 61(1), 1:1\u20131:23 (2014)","DOI":"10.1145\/2529989"},{"key":"11_CR8","doi-asserted-by":"publisher","first-page":"449","DOI":"10.4153\/CJM-1965-045-4","volume":"17","author":"J Edmonds","year":"1965","unstructured":"Edmonds, J.: Paths, trees and flowers. Can. J. Math. 17, 449\u2013467 (1965)","journal-title":"Can. J. Math."},{"key":"11_CR9","doi-asserted-by":"crossref","unstructured":"Gabow, H.N.: A scaling algorithm for weighted matching on general graphs. In: Proceedings of the 26th IEEE Symposium on Foundations of Computer Science (FOCS), pp. 90\u2013100 (1985)","DOI":"10.1109\/SFCS.1985.3"},{"issue":"4","key":"11_CR10","doi-asserted-by":"publisher","first-page":"773","DOI":"10.1080\/10618600.2018.1442342","volume":"27","author":"S Gallagher","year":"2018","unstructured":"Gallagher, S., Richardson, L.F., Ventura, S.L., Eddy, W.F.: SPEW: Synthetic populations and ecosystems of the world. J. Comput. Graph. Stat. 27(4), 773\u2013784 (2018). https:\/\/doi.org\/10.1080\/10618600.2018.1442342","journal-title":"J. Comput. Graph. Stat."},{"key":"11_CR11","unstructured":"Geographic Information Science and Technology, Oak Ridge National Laboratory: Landsca. https:\/\/landscan.ornl.gov\/"},{"key":"11_CR12","unstructured":"Gridded Population of the World (GPW), v4. https:\/\/sedac.ciesin.columbia.edu\/data\/collection\/gpw-v4"},{"key":"11_CR13","doi-asserted-by":"publisher","first-page":"444","DOI":"10.1016\/j.tra.2020.10.006","volume":"141","author":"BY He","year":"2020","unstructured":"He, B.Y., Zhou, J., Ma, Z., Chow, J.Y., Ozbay, K.: Evaluation of city-scale built environment policies in New York City with an emerging-mobility-accessible synthetic population. Transp. Res. Part A Policy Pract. 141, 444\u2013467 (2020)","journal-title":"Transp. Res. Part A Policy Pract."},{"key":"11_CR14","unstructured":"HERE Premium Streets Data set for the U.S. (2020). https:\/\/www.here.com\/"},{"key":"11_CR15","unstructured":"IDM: Synthpops (2025). https:\/\/docs.idmod.org\/projects\/synthpops\/en\/latest\/"},{"key":"11_CR16","doi-asserted-by":"crossref","unstructured":"Islam, K.A., et al.: Incorporating fairness in large-scale evacuation planning. In: Proceedings of the 31st ACM International Conference on Information and Knowledge Management, pp. 3192\u20133201. New York, NY, USA (2022)","DOI":"10.1145\/3511808.3557075"},{"key":"11_CR17","doi-asserted-by":"crossref","unstructured":"Islam, K.A., Marathe, M., Mortveit, H., Swarup, S., Vullikanti, A.: A simulation-based approach for large-scale evacuation planning. In: IEEE International Conference on Big Data, 2020, pp. 1338\u20131345 (2020)","DOI":"10.1109\/BigData50022.2020.9377794"},{"issue":"1","key":"11_CR18","doi-asserted-by":"publisher","first-page":"41","DOI":"10.14257\/ijt.2016.4.1.03","volume":"4","author":"K Lum","year":"2016","unstructured":"Lum, K., Chungbaek, Y., Eubank, S.G., Marathe, M.V.: A two-stage, fitted values approach to activity matching. Int. J. Transp. 4(1), 41\u201356 (2016)","journal-title":"Int. J. Transp."},{"key":"11_CR19","unstructured":"Maalouly, N.E.: Exact matching: algorithms and related problems. In: Proc. Symposium on Theoretical Computer Science (STACS), pp. 36:1\u201336:24 (2023)"},{"key":"11_CR20","first-page":"1","volume-title":"Emerging Trends in Predictive Analytics: Risk Management and Decision Making","author":"M Marathe","year":"2014","unstructured":"Marathe, M., Mortveit, H., Parikh, N., Swarup, S.: Prescriptive analytics using synthetic information. In: Hsu, W.H. (ed.) Emerging Trends in Predictive Analytics: Risk Management and Decision Making, pp. 1\u201319. IGI Global, Hershey, PA (2014)"},{"key":"11_CR21","unstructured":"Microsoft: U.S. building footprints (2018). https:\/\/github.com\/Microsoft\/USBuildingFootprints"},{"key":"11_CR22","doi-asserted-by":"crossref","unstructured":"Mistry, D., et al.: Inferring high-resolution human mixing patterns for disease modeling. Nat. Commun. 12(1), 323 (2021)","DOI":"10.1038\/s41467-020-20544-y"},{"key":"11_CR23","unstructured":"National Center for Education\u00a0Statistics (NCES), T.: http:\/\/nces.ed.gov, Accessed Feb 2020"},{"key":"11_CR24","doi-asserted-by":"publisher","DOI":"10.1016\/j.jtrangeo.2020.102902","volume":"90","author":"MM Nejad","year":"2021","unstructured":"Nejad, M.M., Erdogan, S., Cirillo, C.: A statistical approach to small area synthetic population generation as a basis for carless evacuation planning. J. Transp. Geogr. 90, 102902 (2021)","journal-title":"J. Transp. Geogr."},{"key":"11_CR25","unstructured":"OpenStreetMap points of interest. https:\/\/www.openstreetmap.org\/, Accessed 7 Feb 2021"},{"key":"11_CR26","doi-asserted-by":"publisher","DOI":"10.1016\/j.jtbi.2020.110461","volume":"507","author":"M Renardy","year":"2020","unstructured":"Renardy, M., Eisenberg, M., Kirschner, D.: Predicting the second wave of COVID-19 in Washtenaw County. MI. J. Theor. Biol. 507, 110461 (2020)","journal-title":"MI. J. Theor. Biol."},{"key":"11_CR27","doi-asserted-by":"crossref","unstructured":"Tatem, A.: WorldPop, open data for spatial demography. Sci. Data 4 (2017)","DOI":"10.1038\/sdata.2017.4"},{"key":"11_CR28","doi-asserted-by":"crossref","unstructured":"Thorve, S., et a.: High resolution synthetic residential energy use profiles for the United States. Sci. Data 10, 76 (2023)","DOI":"10.1038\/s41597-022-01914-1"},{"key":"11_CR29","unstructured":"US Census: Public use microdata sample (PUMS). https:\/\/www.census.gov\/programs-surveys\/acs\/microdata.html, Accessed 24 May 2021"},{"key":"11_CR30","unstructured":"Virginia Institute of Marine Sciences: Tidewatch (2025). https:\/\/cmap2.vims.edu\/SCHISM\/TidewatchViewer.html"},{"key":"11_CR31","volume-title":"Introduction to Graph Theory","author":"DB West","year":"2001","unstructured":"West, D.B.: Introduction to Graph Theory. Prentice-Hall, Englewood Cliffs, NJ (2001)"},{"key":"11_CR32","doi-asserted-by":"crossref","unstructured":"Wheaton, W.D., et al.: Synthesized population databases: a US geospatial database for agent-based models. Technical report. MR-0010-0905, RTI International, Research Triangle Park, NC, USA (2009)","DOI":"10.3768\/rtipress.2009.mr.0010.0905"}],"container-title":["Lecture Notes in Computer Science","Multi-Agent-Based Simulation XXVI"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-16328-8_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T14:38:12Z","timestamp":1770647892000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-16328-8_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9783032163271","9783032163288"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-16328-8_11","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"10 February 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MABS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Multi-Agent Systems and Agent-Based Simulation","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Detroit, MI","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 May 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 May 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"mabs2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/mabsworkshop.github.io\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}