By C. Tan
ISBN-10: 9537619079
ISBN-13: 9789537619077
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1999). Simulated annealing: an alternative approach to true multiobjective optimization. Proceeding of Genetic and Evolutionary Computation Conference. Conference Workshop Program, pp 406–407, Florida, Orlando. T. J. (2000). A simulated annealing algorithm for multiobjective optimization, Engineering Optimization, vol. 33. pp. 5985, 2000. ; Tuyttens, D. L. (2000). An interactive heuristic method for multiobjective combinatorial optimization, Journal of Comput and Operations Research, vol. 27, pp.
Computers & Operations Research 2007; 34; 30993111. Lian Z, Gu X, Jiao B. A similar particle swarm optimization algorithm for permutation flowshop scheduling to minimize makespan. Applied Mathematics and Computation 2006a; 175; 773-785. Lian Z, Gu X, Jiao B. A similar particle swarm optimization algorithm for job-shop scheduling to minimize makespan. Applied Mathematics and Computation 2006b; 183; 1008-1017. Allahverdi A, Al-Anzi FS. A PSO and a Tabu search heuristics for the assembly scheduling problem of the two-stage distributed database application.
As it is evident from Table 4, parameters N and R are considered as linear functions in terms of the problem size. 01 120 Sec. 10 Table 4. 5 is solved and the best Pareto solutions are reported in Table 5. The average and standard deviation (SD) of TWFT and WfC values associated with the obtained Pareto solutions are also presented in this table. As it is evident from Table 5, the small values of SD imply that the algorithm converges to a small region of the objective space. That means that the distance between the obtained Pareto solutions is insignificant and the solutions have a relatively identical importance degree from the decision making point of view.
Simulated Annealing [math] by C. Tan
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