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Project
• Simulate genetic algorithms and analyze effects of mutations
• General Requirement• Develop a gentle tutorial for the concept of genetic algorithms.• Pick an existing program and modify it.• The system graphically displays the state of each generation with appropriate
statistics that show progress toward the goal.• The system should allow dynamic modification of parameters, operators, and
probabilities.• Add your own genetic operators based on your analysis.• Pick a new problem and create a genetic solution by mutating populations. The
problem should be NP-complete and your results should be compared analytically to a known algorithm that approximates a solution.
Potential Applications of GA
virtually anything where potential solution isa) string of symbolsb) testable for fitness
• Generating automatons• Finding routes• Constructing formulas• Writing War & Peace (not really)• …
Choosing the Problem
Traveling Salesman Problem (TSP):Given a list of cities and a map of the roads• visit each city once,• come back to hometown• use the shortest route.
TSP Solution Process
a) Create initial population of routesb) Assess fitness of each routec) If not satisfactory, create new populationd) Introduce mutation (optional)e) Goto b)
Choosing Implementation
Implementation AssessmentJava Applet / JavaScript seems popular
Server-side (Java/.NET) model and client-side view-controller (JavaScript/HTML)
would be awesome
Standalone desktop application (C#, Window Forms)
could actually work
Generation of Solution
a) select first/last node (using schemata*)b) randomly generate a speciec) test if good (not bad or ugly)d) Repeat
* — zero/one mask
Population Control
• Elitism Rate– % of population selected to be carried over to next
generation without change– Elite gets to procreate too– Discard same % of least performing part of
population• Mutation Rate– % of genes of each new specie that get mutated