dtsp_ga_basic(nStop​s, popSize, numIter, xy, range, speed )

Version 2.0.0 (2.96 KB) by Robert Rich
Truck Drone Traveling Salesman Problem genetic algorithm solver
296 Downloads
Updated 22 Dec 2019

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This genetic algorithm solves the truck drone in tandem team or "last mile" effort for traveling salesman problem for parcel delivery operations (i.e. UPS, FedEx). Each truck carries a drone which is launched from a stop to deliver a parcel within range to a nearby stop while operating in parallel with the truck. The truck and drone work in parallel operations to deliver packages. The drone is constrained by both range and capacity. As such, it must operate in close proximity of the truck as an operation. An operation is when a truck launches the drone, truck and drone deliver to separate locations, and the truck then recovers the drone at a rendezvous location for battery swaps and loading. The idea is to determine a route for truck and drone (as well as operations) that minimizes total time. Total time is based on the times for the operations (launch-deliver-recover). The max time of an operation (truck or drone) is used to calculate total time for the route.

Cite As

Robert Rich (2024). dtsp_ga_basic(nStops, popSize, numIter, xy, range, speed ) (https://www.mathworks.com/matlabcentral/fileexchange/60640-dtsp_ga_basic-nstops-popsize-numiter-xy-range-speed), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2015a
Compatible with R2019b and later releases
Platform Compatibility
Windows macOS Linux
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Version Published Release Notes
2.0.0

Updated with operation fathom

1.4.0.2

Updated the inputs to 5

1.4.0.1

Updated default inputs

1.4.0.0

Improved performance of cost function
cost function efficiency

1.3.0.0

updated cost function for return to depot.

1.2.0.0

Simplified the file

1.1.0.0

Update number hubs

1.0.0.0