hw6 - CEE 5290/COM S 5722 Heuristic Methods for...

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CEE 5290/COM S 5722 Heuristic Methods for Optimization Homework 6: Binary and Real Genetic Algorithm Assigned: Friday, October 7, 2011 Due: Friday, October 14, 2011 TA office hours: Wed 10:00-11:00am, Thu: 3:00- 4:30pm in Hollister 203, Prof. Shoemaker M(2-3), W & F (2:30-3:30), Rm 210 Hollister Readings: Lecture handouts on Real Valued GA and constraint handling in GA; Optional reading is Reed, P., B. Minsker, and D. E. Goldberg, 2000 Designing a competent simple genetic algorithm for search and optimization. Water Resources Research , 36(12): 3757- 3761. Instructions on how to download this paper from the library are in the Assignments folder under HW6 in Blackboard . 1. A 5-bit binary GA with a population size of 4 is used to solve a maximization problem. At generation zero the following information is available to you: Member String Fitness 1 10001 20 2 11001 10 3 00101 5 4 01101 15 The following GA algorithm parameters hold: Probability of crossover = 1 In each crossover operation a one-point crossover strategy with 2 parents will be employed to produce exactly one child. The first part of the genes of the child (bits 1 to the crossover point) will come from the first parent, and the second part (from the crossover point to the end of the string) from the second parent. (a) If roulette wheel selection is employed and if there is no mutation,What is the chance that a member in generation 1 will be of the form 1xxxx? What is the chance that a member in generation 1 will be of the form 0xxxx? Now assume bit-wise mutation probability, pMutation = 0.01 (b) Now assume bit-wise mutation probability, pMutation = 0.01 and no crossover.What is the chance now that a member in generation 1 will be of the form 1xxxx? What is the chance that a member in generation 1 will be of the form 0xxxx? 2.
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hw6 - CEE 5290/COM S 5722 Heuristic Methods for...

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