Article1989

A Break from Tradition for the San Francisco Police: Patrol Officer Scheduling Using an Optimization-Based Decision Support System

140 citations0/0 files storedINFORMS Journal on Applied Analytics

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Scheduling and Timetabling Solutions Healthcare Operations and Scheduling Optimization Facility Location and Emergency Management

Abstract

The San Francisco Police Department (SFPD) recently implemented an optimization-based decision support system for deploying patrol officers. It forecasts hourly needs, schedules officers to maximize coverage, and allows fine tuning to meet human needs. The fine-tuning mode helps captains evaluate schedule changes and suggests alternatives. The system also evaluates policy options for strategic deployment. The integer search procedure generates solutions that make 25 percent more patrol units available in times of need, equivalent to adding 200 officers to the force or a savings of $11 million per year. Response times improved 20 percent, while revenues from traffic citations increased by $3 million per year.

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References

1974A hypercube queuing model for facility location and redistricting in urban emergency services 1986The general employee scheduling problem. An integration of MS and AI 1976Workforce Allocation in Cyclical Scheduling Problems: A Survey 1972A Mathematical Programming Model for Scheduling Nursing Personnel in a Hospital 1972Urban Police Patrol Analysis 1980Cyclic Scheduling via Integer Programs with Circular Ones 1981A Guaranteed-Accuracy Round-off Algorithm for Cyclic Scheduling and Set Covering 1983Simple Approaches to Shift, Days-Off and Tour Scheduling Problems

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1991A Comparative Evaluation of Labor Tour Scheduling Methods 2000Optimal Models for Meal-Break and Start-Time Flexibility in Continuous Tour Scheduling 1999A distributed genetic algorithm for deterministic and stochastic labor scheduling problems 1997Labor staffing and scheduling models for controlling service levels 2008Workforce scheduling with multiple objectives

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