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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.

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Stp an aerial spray treatment planning system

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
Overview of Presentation

  • Abstract

  • How did STP come about

  • Goals of STP

  • Basic architecture

  • Heuristics

  • Overview of STP

  • Conclusion and future developments


Abstract
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 presentation1
Overview of Presentation

  • Abstract

  • How did STP come about

  • Goals of STP

  • Basic architecture

  • Heuristics

  • Overview of STP

  • Conclusion and future developments


How STP came about

  • 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.


Overview of presentation2
Overview of Presentation

  • Abstract

  • How did STP come about

  • Goals of STP

  • Basic architecture

  • Heuristics

  • Overview of STP

  • Conclusion and future developments


Goals of STP

  • 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


airport

blocks


airport

blocks


Goals of STP

  • 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


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 presentation3
Overview of Presentation effectiveness

  • Abstract

  • How did STP come about

  • Goals of STP

  • Basic architecture

  • Heuristics

  • Overview of STP

  • Conclusion and future developments



Overview of presentation4
Overview of Presentation effectiveness

  • Abstract

  • How did STP come about

  • Goals of STP

  • Basic architecture

  • Heuristics

  • Overview of STP

  • Conclusion and future developments


Heuristics effectiveness

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
Flight Advisor effectiveness

If the block = polygon of rectangles then

spray along the longest side of rectangles

else

spray along the longest side of the polygon

endif


Heuristics effectiveness

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 effectiveness

  • 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 effectiveness

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): effectiveness

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): effectiveness

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): effectiveness

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 effectiveness

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


Justification effectiveness

  • 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


Heuristics effectiveness

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
Implementation effectiveness

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


Implementation1
Implementation Serviced by Single Airport

CVRPS -- for multiple blocks serviced by a single airport

CVRPM -- for multiple airports


Capacitated vehicle routing problem for multiple blocks serviced by single airport
Capacitated Vehicle Routing Problem for Multiple Blocks Serviced by Single Airport

  • 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


Overview of presentation5
Overview of Presentation Serviced by Single Airport

  • Abstract

  • How did STP come about

  • Goals of STP

  • Basic architecture

  • Heuristics

  • Overview of STP

  • Conclusion and future developments


Overview of presentation6
Overview of Presentation Serviced by Single Airport

  • Abstract

  • How did STP come about

  • Goals of STP

  • Basic architecture

  • Heuristics

  • Overview of STP

  • Conclusion and future developments


Conclusion & future work Serviced by Single Airport

  • 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

Thanks Serviced by Single Airport


Overview of the presentation
Overview of the Presentation Serviced by Single Airport

  • Abstract

  • How did STP come about

  • Goals of STP

  • Basic architecture

  • Heuristics

  • Overview of STP

  • Conclusion and future developments


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