Download Dark Blue with Orange

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project

Document related concepts

Polymorphism (biology) wikipedia , lookup

History of genetic engineering wikipedia , lookup

Genetic engineering wikipedia , lookup

Genetic code wikipedia , lookup

Human genetic variation wikipedia , lookup

Genetic testing wikipedia , lookup

Genome (book) wikipedia , lookup

Group selection wikipedia , lookup

Genetic drift wikipedia , lookup

Koinophilia wikipedia , lookup

Gene expression programming wikipedia , lookup

Epistasis wikipedia , lookup

Mutation wikipedia , lookup

Frameshift mutation wikipedia , lookup

Point mutation wikipedia , lookup

Microevolution wikipedia , lookup

Population genetics wikipedia , lookup

Transcript
Genetic Algorithms and TSP
Thomas Jefferson Computer Research Project
by Karl Leswing
Genetic Algorithms



Effective in Optimization Problems
Classified as a global search heuristic
Inspired by Evolutionary Biology




Inheritance
Mutation
Selection
Crossover
Traveling Salesman

Given a number of
cities and the costs of
traveling from any city
to any other city, what
is the cheapest roundtrip rout that visits each
city exactly once and
then returns to the
starting city.
Traveling Salesman Continued



O(N!)
Dynamic Programming down to O((n^2)*2^n)
Find Near Optimal Solutions
Current Work
Current Work Continued


Double Point Crossover
Roulette Selection


Single Point Mutation


Unique Fitness Algorithm
Mutation Rate Variable
Effectiveness

Solve 50 City TSP in less than one minute
Extensions

Selections




Matrix Encoding
Mutations



Double Point
Cycle
3 Dimension


Tournament
Elitism
Open GL
Weighted Paths