{"id":{"repo_id":"gatech","oai_identifier":"oai:repository.gatech.edu:1853/62857"},"canonical_url":"https://search.dev.ndltd.org/etd/gatech/oai:repository.gatech.edu:1853/62857","repository":{"repo_id":"gatech","name":"Georgia Tech","base_url":"https://repository.gatech.edu/server/oai/request"},"display":{"title":"Data-driven optimization for police beat design in South Fulton, Georgia","abstract":"We redesign the police patrol beats in South Fulton, Georgia, in collaboration with the South Fulton Police Department (SFPD), using a predictive data-driven optimization approach. Due to rapid urban development and population growth, the original police beats arrangement designed in the 1970s was far from efficient, which leads to low policing efficiency and long 911 call response time. We balance the police workload among different regions in the city, improve operational efficiency, and reduce 911-call response time by redesigning beat boundaries for the SFPD. We discretize the city into small geographical atoms, which correspond to our decision variables; the decision is to map the atoms into \"beats\", which are the basic units of the police operation. We analyze workload and trend in each atom using the rich dataset for police incidents reports and U.S. census data and predict future police workload for each atom using spatial statistical regression models. Basing on this, we formulate the optimal beat design as a mixed-integer programming (MIP) program with contiguity and compactness constraints on the shape of the beats. The optimization problem is solved using simulated annealing due to its large-scale and non-convex nature. Our resulted beat design can reduce workload variance by over 90% according to our simulation. Our new optimal beat design has been approved by the City Council of South Fulton and implemented in January 2020.","abstract_html":"We redesign the police patrol beats in South Fulton, Georgia, in collaboration with the South Fulton Police Department (SFPD), using a predictive data-driven optimization approach. Due to rapid urban development and population growth, the original police beats arrangement designed in the 1970s was far from efficient, which leads to low policing efficiency and long 911 call response time. We balance the police workload among different regions in the city, improve operational efficiency, and reduce 911-call response time by redesigning beat boundaries for the SFPD. We discretize the city into small geographical atoms, which correspond to our decision variables; the decision is to map the atoms into "beats", which are the basic units of the police operation. We analyze workload and trend in each atom using the rich dataset for police incidents reports and U.S. census data and predict future police workload for each atom using spatial statistical regression models. Basing on this, we formulate the optimal beat design as a mixed-integer programming (MIP) program with contiguity and compactness constraints on the shape of the beats. The optimization problem is solved using simulated annealing due to its large-scale and non-convex nature. Our resulted beat design can reduce workload variance by over 90% according to our simulation. Our new optimal beat design has been approved by the City Council of South Fulton and implemented in January 2020.","abstract_has_math":false,"creators":["Lu, Le"],"institution":"Georgia Institute of Technology","degree_name":null,"degree_level":"Masters","degree_discipline":null,"degree_department":"Industrial and Systems Engineering","school":null,"contributors":[],"advisors":["Xie, Yao"],"committee_chairs":[],"committee_members":["Wang, He","Dey, Santanu S."],"year":2020,"date_issued":"2020-04-28","date_published":"2020-04-28","updated_at":"2026-07-27T19:51:09Z","subjects":["Data-driven optimization","Predictive policing","Police beat redesign"],"languages":["en_US"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1853/62857","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Xie, Yao"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Wang, He","Dey, Santanu S."]},{"key":"dc:contributor.department","label":"Department","values":["Industrial and Systems Engineering"]},{"key":"dc:creator","label":"Author","values":["Lu, Le"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2020-05-20T17:04:12Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2020-05-20T17:04:12Z"]},{"key":"dc:date.issued","label":"Date","values":["2020-04-28"]},{"key":"dc:publisher","label":"Institution","values":["Georgia Institute of Technology"]},{"key":"dc:type","label":"Dc Type","values":["Text"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Masters"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Data-driven optimization","Predictive policing","Police beat redesign"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en_US"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1853/62857"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["We redesign the police patrol beats in South Fulton, Georgia, in collaboration with the South Fulton Police Department (SFPD), using a predictive data-driven optimization approach. Due to rapid urban development and population growth, the original police beats arrangement designed in the 1970s was far from efficient, which leads to low policing efficiency and long 911 call response time. We balance the police workload among different regions in the city, improve operational efficiency, and reduce 911-call response time by redesigning beat boundaries for the SFPD. We discretize the city into small geographical atoms, which correspond to our decision variables; the decision is to map the atoms into \"beats\", which are the basic units of the police operation. We analyze workload and trend in each atom using the rich dataset for police incidents reports and U.S. census data and predict future police workload for each atom using spatial statistical regression models. Basing on this, we formulate the optimal beat design as a mixed-integer programming (MIP) program with contiguity and compactness constraints on the shape of the beats. The optimization problem is solved using simulated annealing due to its large-scale and non-convex nature. Our resulted beat design can reduce workload variance by over 90% according to our simulation. Our new optimal beat design has been approved by the City Council of South Fulton and implemented in January 2020."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["M.S."]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Data-driven optimization for police beat design in South Fulton, Georgia"]}]}],"canonical_facts":{"dc:contributor.advisor":["Xie, Yao"],"dc:contributor.committeemember":["Wang, He","Dey, Santanu S."],"dc:contributor.department":["Industrial and Systems Engineering"],"dc:creator":["Lu, Le"],"dc:date.accessioned":["2020-05-20T17:04:12Z"],"dc:date.available":["2020-05-20T17:04:12Z"],"dc:date.issued":["2020-04-28"],"dc:description.abstract":["We redesign the police patrol beats in South Fulton, Georgia, in collaboration with the South Fulton Police Department (SFPD), using a predictive data-driven optimization approach. Due to rapid urban development and population growth, the original police beats arrangement designed in the 1970s was far from efficient, which leads to low policing efficiency and long 911 call response time. We balance the police workload among different regions in the city, improve operational efficiency, and reduce 911-call response time by redesigning beat boundaries for the SFPD. We discretize the city into small geographical atoms, which correspond to our decision variables; the decision is to map the atoms into \"beats\", which are the basic units of the police operation. We analyze workload and trend in each atom using the rich dataset for police incidents reports and U.S. census data and predict future police workload for each atom using spatial statistical regression models. Basing on this, we formulate the optimal beat design as a mixed-integer programming (MIP) program with contiguity and compactness constraints on the shape of the beats. The optimization problem is solved using simulated annealing due to its large-scale and non-convex nature. Our resulted beat design can reduce workload variance by over 90% according to our simulation. Our new optimal beat design has been approved by the City Council of South Fulton and implemented in January 2020."],"dc:description.degree":["M.S."],"dc:format.mimetype":["application/pdf"],"dc:identifier.uri":["http://hdl.handle.net/1853/62857"],"dc:language.iso":["en_US"],"dc:publisher":["Georgia Institute of Technology"],"dc:subject":["Data-driven optimization","Predictive policing","Police beat redesign"],"dc:title":["Data-driven optimization for police beat design in South Fulton, Georgia"],"dc:type":["Text"],"thesis:degree_level":["Masters"]},"updated_at":"2026-07-27T19:51:09Z"}