GLOBAL OPTIMIZATION OF PUMP CONFIGURATION PROBLEM USING EXTENDED CROWDING GENETIC ALGORITHM

摘要

＜正＞ An extended crowding genetic algorithm （ECGA） is introduced for solving optimal pumpconfiguration problem, which was presented by T.Westerlund in 1994. This problem has been found tobe non-convex, and the objective hation contained several local optima and global optimality couldnot be ensured by all the traditional MINLP optimization method. The concepts of species conservingand composite encoding are introduced to crowding genetic algorithm （CGA） for mantain the diver-sity of population more effectively and coping with the continuous and/or discrete variables in MINLPproblem. The solution of three-levels pump configuration got from DICOPT++ software （OA algo-rithm） is also given. By comparing with the solutions obtained from DICOPT++, ECP method, andMIN-MIN method, the ECGA algorithm proved to be very effective in finding the global optimalsolution of multi-levels pump configuration via using the problem-specific information.