- Discuss different survival selection - Discuss different cross-over method - What are the possible solutions to jump scape from local minimums or maximums in GA - Find an application that has been optimized using genetic algorithm. - For what applications GA performs better.
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7. GENETIC ALGORITHMS (a) Write down a sequence of the letters A to I in such an order that the following steps sorted in this way would give a top level description of a Genetic Algorithm: A) Repeat B) Pick parent chromosomes. C) Evaluate each chromosome in the initial population. D) Delete members of the population to make room for the new chromosomes. E) Evaluate the children chromosomes and insert them into the population. F) Generate an initial population of chromosomes. G) Return the best chromosome. H) Apply mutation and crossover as the parent chromosomes mate. I) Until problem is solved or time is up Answer the following questions in only one sentence each. (b) Which of the steps need to know about the application? (c) In which of the steps does selectivity play a role? (d) What is the disadvantage of being too selective? (e) Should in general the influence of crossover increase or decrease during evolution? (f) Consider an application of the ‘Genetic Algorithm’ (GA) where chromosomes are binary strings of length 8. Explain, in one sentence each, what the defining length δ(H) and the order o(H) of a schema H is. Give the defining length and the order for the following schemata:
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For the Octave/Matlab fmincon function: - What optimization problems can you use it for? - What methods do you use? For the genetic algorithm in solving optimization problems: - What advantages does the genetic algorithm have over fmincon? - What are the principles of its operation?
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