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HW2 - CEE 5290/COM S 5722/ORIE 5340 Heuristic Methods for...

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CEE 5290/COM S 5722/ORIE 5340 Heuristic Methods for Optimization Homework 2: Simulated Annealing Assigned: Wednesday , September 7, 2011 Due: Wednesday, September 14, 2011-handed in before class TA Office Hours: Thurs (9/8) 3:00-4:30pm Tues (9/13) 3:00-4:30pm, in Hollister 203 Professor Shoemaker office hours : MWF 3-4, Hollister 210 IMPORTANT: In the interest of being able to answer everyone’s questions on the HW promptly (this is a big class), please post your questions on the Blackboard Discussion Board under the heading ‘Questions on HW 2’. There is also a separate heading for general questions that students can post about the class. Please title and state your questions clearly and concisely so that other members of the class may also benefit from your questions. The TA will try to address the questions within 24 hours of the questions being posted. Please email the TA only about matters that cannot be done on Blackboard like homework extensions and other course administration issues. NOTE: The Simulated Annealing (SA) algorithm and metropolis procedure given on page 54 of the text (Figures 2.3 and 2.4) are reprinted below with the corrections that are missing in the text. You will implement these algorithms directly for questions in this HW. Check the Blackboard website regularly for hints or corrections, if any. Algorithm Simulated_annealing( S 0 , T 0 , α , β , M, Maxtime ); % S 0 or sinitial is the initial solution % BestS is the best solution % T 0 or Tinitial is the initial temperature % α or alpha is the cooling rate % β is a constant % M represents the time until the next parameter update % Maxtime is the maximum total time for annealing process % Time refers to the number of cost function evaluations performed Begin T = T 0 ; CurS = S 0 ; BestS = CurS ; % BestS is the best solution seen so far CurCost = Cost ( CurS ); BestCost = CurCost ; % CORRECTION Time = 0; Repeat Call Metropolis( CurS , CurCost , BestS , BestCost , T , M ); Time = Time + M ; T = α T ; % Update T after M iterations M = β M ; Until ( Time Maxtime ) Return ( solution, BestS ); % CORRECTION End of Simulated Annealing
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Algorithm Metropolis( CurS , CurCost , BestS , BestCost , T , M ); Begin M1 = M ; Repeat NewS = Neighbor ( CurS
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