Consider the following single machine scheduling problem: jobs 1 Pj (processing time) 9 d; (deadline) w;...

 

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Consider the following single machine scheduling problem: jobs 1 Pj (processing time) 9 d; (deadline) w; (weight) 2 3 9 12 10 8 5 14 12 1 4322 28 Apply the Simulated Annealing to the problem with an initial solution (sequence) 3-1-4-2. The stopping condition is identified as the maximum number of iterations (tmax = 3). Choose a(t) = 0.9t as the cooling schedule and to = 0.9 as the initial temperature. Neighbors should be generated by using adjacent pairwise interchanges. Randomly select a neighbor within the neighborhood. Use the following ordered numbers as random numbers: 0.17, 0.91, 0.61, 0.66, 0.7, 0.41, 0.07, 0.13, 0.48, 0.51, 0.94, 0.23, 0.15, 0.58. a) Solve the problem such that its objective is to minimize the total weighted tardiness. b) Solve the problem such that its objective is to minimize maximum tardiness (Ignore the weights in this case). c) Solve the problem with weighted tardiness objective using Tabu Search, where the stopping condition is identified as the maximum number of iterations (tmax = 3) and tabu tenure is 2 Activate Windo gs to activate W Consider the following single machine scheduling problem: jobs 1 Pj (processing time) 9 d; (deadline) w; (weight) 2 3 9 12 10 8 5 14 12 1 4322 28 Apply the Simulated Annealing to the problem with an initial solution (sequence) 3-1-4-2. The stopping condition is identified as the maximum number of iterations (tmax = 3). Choose a(t) = 0.9t as the cooling schedule and to = 0.9 as the initial temperature. Neighbors should be generated by using adjacent pairwise interchanges. Randomly select a neighbor within the neighborhood. Use the following ordered numbers as random numbers: 0.17, 0.91, 0.61, 0.66, 0.7, 0.41, 0.07, 0.13, 0.48, 0.51, 0.94, 0.23, 0.15, 0.58. a) Solve the problem such that its objective is to minimize the total weighted tardiness. b) Solve the problem such that its objective is to minimize maximum tardiness (Ignore the weights in this case). c) Solve the problem with weighted tardiness objective using Tabu Search, where the stopping condition is identified as the maximum number of iterations (tmax = 3) and tabu tenure is 2 Activate Windo gs to activate W