Abstract: In this paper, we investigate on a derivative-free optimization approach, simulated annealing (SA), for the optimization of the reactive distillation (RD) column design. Because RD systems exhibit non-monotonic behavior for key design variables, flowsheet optimization using simulator is difficult when derivative-based approach is employed. The SA-based optimization procedure gives an equally good or better design than the optimal flowsheet obtained from the sequential design approach. More importantly, this is achieved with much more efficient computing. [Copyright &y& Elsevier]
Abstract: This paper concerns a minimax model to investigate the optimal portfolio selection problem without riskless assets and with or without short sale restriction. A numerical solution to the problem with short sale restriction is obtained by using the maximum entropy algorithm. For the problem without short sale restriction, we derive a analytical expression for the optimal solution, a sufficient condition for the existence and uniqueness of a nonnegative equilibrium price system, and an explicit formula for the price system. Furthermore, a numerical example is given to show the validity of the method. [Copyright &y& Elsevier]
Abstract: In this paper, we study the conditions in which the random hill-climbing algorithm (1 + 1)-EA compares favorably to other evolutionary algorithms (EAs) in terms of fitness function distribution at a given iteration and with respect to the average optimization time. Our approach is applicable when the reproduction operator of an evolutionary algorithm is dominated by the mutation operator of the (1 + 1)-EA. In this case one can extend the lower bounds obtained for the expected optimization time of the (1 + 1)-EA to other EAs based on the dominated reproduction operator. This method is demonstrated on the sorting problem with HAM landscape and the exchange mutation operator. We consider several simple examples where the (1 + 1)-EA is the best possible search strategy in the class of the EAs. [Copyright &y& Elsevier]