Repurposing RouteSmart’s Park- and-Loop Tool: Building ......320K residences served weekly...
Transcript of Repurposing RouteSmart’s Park- and-Loop Tool: Building ......320K residences served weekly...
Repurposing RouteSmart’s Park-
and-Loop Tool: Building Innovative
Litter Abatement Routes
Leonard Huggins, PhD
City of Charlotte
Solid Waste Services
Overview
Operational Problem
Goals
Approach
Results
Lessons Learned
Outline: Managing the Plan
Benchmarking all streets with litter control service
(desired and actual)
SWS consistently ranks below the state average in collection costs and complaints
320K residences served weekly
Collected in FY2013
250 thousand tons of garbage
49 thousand tons of yard waste
48 thousand tons of recycling
City of Charlotte | Solid Waste Services
City of Charlotte and Mecklenburg County Official
Government Website. URL: http://charmeck.org
Develop Efficient Litter Control Routes
No existing optimized routes
Different service levels required
Limited staffing (max 18; avg. 11)
Diverse, varying demand
Miles of road to service
Need to collection data to inform
Public service
Resource management
Routing or Operational Challenge
Litter control crews at work
Develop systematic, optimized litter control routes that meet current resource allocations;
Identify and provide minimum level of service in lightly littered areas;
Identify and provide an elevated level of service in litter-inflicted areas;
Collect data that provide statistics for neighborhood awareness and educational campaigns (over time)
Identify hotspots (over time)
Project Goals
Other working team members Technology Manager
Director of Operations
GIS Technician
Field Operations Supervisors
Several Litter Control Crew Members
Approach 1: Build a Team
Map all streets serviced
Iterative benchmarking process
Highlight streets on paper map
Update streets layer
Determine miles of road to be serviced
648 miles
Determine regions
Two; later three
Determine level of affordable service
2 vs. 3 person crews
Optimize & customize routes
Approach 2: Work Flow
Driver reviewing map at a park
point
Designing regions
Core (1): 2 regions (bi-weekly service)
5 days per region
5 routes per day
Periphery (2) 4 regions (service every 4 weeks) 5 days per region
1 route per day
Total 3 regions every day
7 daily routes
Dense Network of
Streets Bi-Weekly Park & Loop
Routing Strategies
Sparse Network of
Streets Monthly Leap Frog
Density Service Level Route Design
Route Design
Park and Loop
Crew flexibility
2, 3 or 5 person crews
Densely woven street network (Core)
Required Crew
3 person crews only
Mainly long corridors (Periphery)
Leap Frog
Week # Routes
Average # of Sides
per Route
Average # of Segments
Average # of Miles Per
Route
Miles per crew member per
day
1 5 98 49 9.9 5 or less
2 5 100 50 8.7 4.3 or less
Core (Park and Loop): Zone 1
9.6 miles per day per route
4.8 miles per crew member
½ to 2/3 miles per hour per crew
(service time 0.15; industry baseline 0.2)
Zone 1 – Week 1 - Mondays
Park and Loop: Grouping Park Points
Customization: “Worker Bee” Tools
Use to
assign the
listed
sequence
number to a
segment.
View
summary
statistics
table one
loop at a
time.
Use this tool
to change
the walking
direction on
a segment.
Use this tool
to move the
park point
to a
different
point.
Three person – crew
1 Driver; 2 Collectors
Periphery: Leap Frog
Litter control crews separating recyclables (yellow
bag) from garbage (black bag) as they collect litter.
Leap Frog
Periphery (Leapfrog): Zone 2
Week # Routes
Average # of Sides
per Route
Average # of Segments
Average # of Miles Per
Route
Miles per crew member per
day
1 1 76 38 7.2 3.6 or less
2 1 92 46 7.2 3.6 or less
3 1 86 43 6.7 3.4 or less
4 1 88 44 6.3 3.2 or less
Managing the Schedule Chaos
A single end-of-day weight would not suffice for neighborhood specific data (not granular enough)
Set count points on the route map:
Park and loop routes
At every loop
At every park point
Leapfrog routes
At every series of park points
Harnessing Data from the Collection Chaos
Counted number of bags
Redistributed total weight as a per bag weight (provided both weight and volume measures)
Total miles covered
Weighted:
Bags per loop per hour
Miles per hour
Change Element
Change in bags collected per loop over time (community level change)
Productivity Matters … Regardless of Chaos
Baseline critical to optimization success
Many iterations to find “true” benchmarks
Customization of optimization product essential to get user buy-in
Using block #s instead of sequence
Utilize granular measures that capture data relevant to route improvement and business efforts
Lessons Learned