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Zhang Guijun
Wu Tihua
College of Electronic and
Electric Engineering,
Shanghai Jiaotong University,
Shanghai 200030, China
Ye Rong
Hebei Academy of Sciences,
Shijiazhuang 050081, China |
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GLOBAL OPTIMIZATION OF PUMP
CONFIGURATION PROBLEM USING
EXTENDED CROWDING GENETIC
ALGORITHM*
Abstract:
An extended crowding genetic algorithm (ECGA) is introduced for solving optimal pump configuration problem, which was presented by T. Westerlund in 1994. This problem has been found to be non-convex, and the objective function contained several local optima and global optimality could not be ensured by all the traditional MINLP optimization method. The concepts of species conserving and composite encoding are introduced to crowding genetic algorithm (CGA) for maintain the diversity of population more effectively and coping with the continuous and/or discrete variables in MINLP problem. The solution of three-levels pump configuration got from DICOPT++ software (OA algorithm) is also given. By comparing with the solutions obtained from DICOPT++, ECP method, and MIN-MIN method, the ECGA algorithm proved to be very effective in finding the global optimal solution of multi-levels pump configuration via using the problem-specific information.
Key words: Pump configuration problem Extended crowding genetic algorithm Species conserving Composite encoding Global optimization
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