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首页> 外文期刊>Journal of food engineering >Multi-objective optimization based on the Utopian point method applied to a case study of osmotic dehydration of plums and its storage
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Multi-objective optimization based on the Utopian point method applied to a case study of osmotic dehydration of plums and its storage

机译:基于乌托邦点法的多目标优化在李子渗透脱水及其存储中的应用

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In this study, authors present the results of multi-objective optimization of parameters of osmotic dehydration of plum and its storage conditions. Multi-objective optimization is a method of multiple criteria decision making involving more than one objective function to be optimized simultaneously. The objective functions are conflicting and an infinite number of Pareto optimal solutions are possible. A solution is Pareto optimal if none of the objective functions can be improved in value without degrading some of the other objective values. All Pareto optimal solutions are considered equally good, the choice is subjective. To limit subjectivism the Utopian point method and Multidimensional Euclidean metrics was applied. The idea is to minimize the distance between the non-existing Utopian solution and Pareto-optimal solutions. This approach is offered in relation to the cost of osmotic solution, time of dehydration process, and duration of storage by considering the following factors: content of dry mass, reducing sugars, and extract, as well as the amount leak after thawing. Authors made the choice of minimizing cost with simultaneous maximization of quality of the product. Pareto-optimal solutions were obtained with the use of MATLAB program. Furthermore, the method of multidimensional Euclidean preferences was applied to find the set of best parameters for the production process. Two sets of results were obtained. First is the set of optimal process parameters is in relation to cost minimizing: concentration of an osmotic solution: 0.55%; time of osmotic draining:, 1 h 42 min; time of the cold storage: 6 months; and the method of thawing: microwave. Second set is focused on quality and process parameters are: the concentration of an osmotic solution: 0.65%; time of osmotic draining:3 h; time of the cold storage: 5 months and 21 days; method of thawing: microwave.
机译:在这项研究中,作者介绍了李子的渗透脱水参数及其存储条件的多目标优化结果。多目标优化是一种多准则决策方法,涉及多个要同时优化的目标函数。目标函数是冲突的,并且可能有无数的帕累托最优解。如果在不降低某些其他目标值的前提下不能提高目标函数的值,则解决方案是帕累托最优的。所有帕累托最优解都被认为是同样好的,选择是主观的。为了限制主观主义,应用了乌托邦点方法和多维欧几里得度量。这个想法是使不存在的乌托邦解和帕累托最优解之间的距离最小。通过考虑以下因素来提供与渗透溶液的成本,脱水过程的时间和保存时间有关的这种方法:干物质的含量,还原糖和提取物的含量,以及解冻后的泄漏量。作者选择了在将成本最小化的同时将产品质量最大化的选择。使用MATLAB程序获得帕累托最优解。此外,使用多维欧几里德偏爱的方法来找到用于生产过程的最佳参数集。获得了两组结果。首先是与降低成本相关的最佳工艺参数集:渗透溶液浓度:0.55%;渗透排水时间:1小时42分钟;冷藏时间:6个月;解冻的方法:微波。第二组集中于质量和工艺参数是:渗透溶液的浓度:0.65%;渗透排水时间:3 h;冷藏时间:5个月21天;解冻方法:微波。

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