STP: An Aerial Spray Treatment Planning System W.D. Potter, Ramyaa, J. Li Artificial Intelligence...
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Transcript of STP: An Aerial Spray Treatment Planning System W.D. Potter, Ramyaa, J. Li Artificial Intelligence...
STP: An Aerial Spray Treatment Planning System
W.D. Potter, Ramyaa, J. Li
Artificial Intelligence Center, GSRC 111
University of Georgia, Athens, GA 30602
(Contact: [email protected] or 706-542-0361)
And
J. Ghent, D. Twardus, H. Thistle
USDA Forest Service
Overview of Presentation
• Abstract
• How did STP come about
• Goals of STP
• Basic architecture
• Heuristics
• Overview of STP
• Conclusion and future developments
Abstract
• The Spray Treatment Planner – an intelligent decision support system for aerial spray treatment.
• A tool to schedule spraying pesticides aerially - a capacitated vehicle router
• STP schedules the spraying operation of selected blocks from selected airports using single or multiple aircraft.
• The scheduling is done to maximize the spray efficiency and spray productivity by minimizing the total time and distance flown.
• It uses heuristics to obtain a near optimal solution.
Overview of Presentation
• Abstract
• How did STP come about
• Goals of STP
• Basic architecture
• Heuristics
• Overview of STP
• Conclusion and future developments
• The gypsy moth (Lymantria dispar L.) has been one of north American’s most devastating forest pests.
• Application of pesticides by aircraft.• Determining the production needs - guess work or
heuristics from other projects.• Over-estimating contract needs - larger than needed
aircraft or more aircraft than needed.• Under-estimating contract needs - treatment at less than
optimal timing.• Needs careful preparation and planning, as well as
comparing different spray application strategies.• A classic problem to be solved by AI techniques.
How STP came about
Overview of Presentation
• Abstract
• How did STP come about
• Goals of STP
• Basic architecture
• Heuristics
• Overview of STP
• Conclusion and future developments
• STP – a capacitated vehicle router
• Attempts to give an optimal schedule for spraying
• Schedule is restricted by fuel and pesticide tank capacity
• Comparison of different schedules
• Gives a realistic estimate of productivity and needs
• Comparison of productivity of various aircraft
explain
Goals of STP
airport
blocks
airport
blocks
• STP – a capacitated vehicle router
• Gives an optimal schedule for spraying
• Schedule is restricted by fuel and pesticide tank capacity
• Comparison of different schedules
• Gives a realistic estimate of productivity and needs
• Comparison of productivity of various aircraft
explain
Goals of STP
Optimal schedule : Quantitative measures of effectiveness
Spray productivity = area sprayed
total aerial spray operation time Spray efficiency = time spent spraying
total aerial spray operation time
Total aerial = time spent + ferry
spray time spraying time
Optimize : ferry time ; time spent spraying
Overview of Presentation
• Abstract
• How did STP come about
• Goals of STP
• Basic architecture
• Heuristics
• Overview of STP
• Conclusion and future developments
The evaluation model flowchart
Overview of Presentation
• Abstract
• How did STP come about
• Goals of STP
• Basic architecture
• Heuristics
• Overview of STP
• Conclusion and future developments
Heuristics
Minimize total flying distance
Minimize time spent in a block :
“Flight Advisor” for a single block
Minimize ferry time
representation
core of the heuristics
justification
implementation
Flight Advisor
If the block = polygon of rectangles thenspray along the longest side of rectangles
else spray along the longest side of the
polygon endif
Heuristics
Minimize total flying distance Minimize time spent in a block : “Flight Advisor” for a single block
Minimize ferry time representation core of the heuristics justification implementation
Representation
• G = {V,E} – a connected graph• V = {V1-Vn} a block set• E = {(Vi,Vi)} a set of flight lines• Lij – length of flight line Vi-Vj• Qi – load associated with Vi• Minimize a linear combination of total
distance traveled by different aircraft• Restricted by pesticide and fuel capacity
Heuristics
Minimize total flying distance Minimize time spent in a block : “Flight Advisor” for a single block
Minimize ferry time representation core of the heuristics justification implementation
Case 1 (typical case): The blocks are on the same side of the airport
but the airport and the blocks are not in the same line. The total saved flight distance is: D1+D2-D3.
Distance saved =D1+D2-D3
Case 2 (worst case):The blocks are on different sides of the airport,
and the airport and blocks are in one line so that the total reduced distance is 0.
Nothing saved
Case 3 (best case):The blocks are on the same side and in the same
line with respect to the airport.
The total saved distance in this case is D1+D2+D3.
Heuristics
Minimize total flying distance Minimize time spent in a block : “Flight Advisor” for a single block
Minimize ferry time representation core of the heuristics justification implementation
• The Capacitated Vehicle Routing Problem is the Traveling Salesperson Problem with additional constraints of capacity
• Exact calculation is not possible for large inputs
• Basnet (1997) gives 2 heuristics and shows that heuristics give reasonably close answers to the exact ones
Justification
Heuristics
Minimize total flying distance Minimize time spent in a block : Flight Advisor” for a single block
Minimize ferry time representation core of the heuristics justification implementation
Implementation
CVRPS -- for multiple blocks serviced by a single airport
CVRPM -- multiple airports
Capacitated Vehicle Routing Problem for Multiple Blocks Serviced by Single Airport
•Forms initial runs such that each run services a single block and associates runs to blocks
•For each run
1) try combining the closest block
2) combination successful if the capacity constraints are met
•for each run (new combined run) calculate the full schedule as a collection of runs and choose the best
Implementation
CVRPS -- for multiple blocks serviced by a single airport
CVRPM -- for multiple airports
• An extension of CVRPS using one airport as base or home airport and the rest for fueling or restocking pesticides.
• Works by relaxing the constraints in capacity
Capacitated Vehicle Routing Problem for Multiple Blocks Serviced by Single Airport
Overview of Presentation
• Abstract
• How did STP come about
• Goals of STP
• Basic architecture
• Heuristics
• Overview of STP
• Conclusion and future developments
Overview of Presentation
• Abstract
• How did STP come about
• Goals of STP
• Basic architecture
• Heuristics
• Overview of STP
• Conclusion and future developments
Conclusion & future work
•The spray advisor uses heuristic methods to find near optimal schedules for spraying selected blocks
•This project is in progress
•Some of the future areas of development involve
1)Considering the terrain to be sprayed
2)Considering mixed aircraft
3)Considering preferred direction of flight
Thanks
Overview of the Presentation
• Abstract
• How did STP come about
• Goals of STP
• Basic architecture
• Heuristics
• Overview of STP
• Conclusion and future developments