Optimal feeding profile in fed-batch bioreactors using a genetic algorithm

被引:2
|
作者
Mokeddem, D. [1 ]
Khellaf, A. [1 ]
机构
[1] Univ Setif, Dept Elect, Fac Engn, Setif 19000, Algeria
关键词
activity based costing; design of experiments; design for manufacture; availability; capability indices; computer vision; control charts; robotics; MULTIOBJECTIVE OPTIMIZATION; FERMENTATION;
D O I
10.1080/00207540903280564
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
An optimal feeding profile for a fed-batch process was designed based on an evolutionary algorithm. Usually the presence of multiple objectives in a problem leads to a set of optimal solutions, commonly known as Pareto-optimal solutions. Evolutionary algorithms are well suited for deriving multi-objective optimisation since they evolve a set of non-dominated solutions distributed along the Pareto front. Several evolutionary multi-objective optimisation algorithms have been developed, among which the Non-dominated Sorting Genetic Algorithm NSGA-II is recognised to be very effective in overcoming a variety of problems. To demonstrate the applicability of this technique, an optimal control problem from the literature was solved using several methods considering the single-objective dynamic optimisation problem.
引用
收藏
页码:6125 / 6135
页数:11
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