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首页> 外文期刊>International Journal of Thermal Sciences >Multi-objective optimization of the design of two-stage flash evaporators: Part 2. Multi-objective optimization
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Multi-objective optimization of the design of two-stage flash evaporators: Part 2. Multi-objective optimization

机译:两级闪蒸蒸发器设计的多目标优化:第2部分。

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摘要

Flash evaporation process is currently developing in the wine industry where it is used for flash-cooling or concentration. The design of flash evaporators is faced with specific constraints and must take into account multiple design objectives. In this paper, the development of a multi-objective optimization method is investigated for the joint optimization of design objectives such as process transportability, environmental efficiency, operative cost or cooling power. The optimization method is based on the aggregation of design objectives through desirability functions and indexes. Desirability functions are suitable for formulating design constraints more precisely than inequality relations and, moreover, the global design model results in an unconstrained optimization problem. However, aggregation methods do make it difficult to compute the global optimum of the design problem. This difficulty has been addressed by developing a distributed genetic algorithm which is not so sensitive to this type of numerical solving difficulty. Another difficulty arises from the weighting method for the aggregation of desirability functions since weight parameters have no physical meaning. This weighting problem is approached through a sensitivity analysis of the weight parameters and by observing their relative influence.
机译:葡萄酒行业目前正在开发闪蒸工艺,该工艺用于闪蒸冷却或浓缩。闪蒸器的设计面临特定的限制,必须考虑多个设计目标。在本文中,研究了一种多目标优化方法的开发,用于联合优化设计目标,例如过程可运输性,环境效率,运营成本或冷却能力。优化方法基于通过合意函数和指标的设计目标的汇总。期望函数比不等式关系更适合于更精确地制定设计约束,而且,全局设计模型会导致无约束的优化问题。但是,聚合方法确实使计算设计问题的全局最优值变得困难。通过开发一种分布式遗传算法已经解决了这一难题,该算法对这种类型的数值求解难题不太敏感。由于权重参数没有物理意义,因此另一种困难由用于合意函数的加权方法引起。通过权重参数的敏感性分析并观察其相对影响来解决此权重问题。

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