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Two-criterion identification of kinetic parameters of olefin hydroalumination by HAlBui2 and ClAlBui2
Engineering Education # 12, December 2013
DOI: 10.7463/1213.0645511
This work was carried out in the context of investigation and development of original two-component neutral catalyst systems made of mixed-valence metal compounds (titanium and zirconium) and organoaluminum compounds. A problem of identification of kinetic parameters of olefin hydroalumination, which belongs to a class of inverse problems of chemical kinetics, was considered in this paper. As a rule, identification problem is formulated as a single-criterion optimization problem for residuals between calculations and experimental data. The disadvantage of such a formulation consists in the fact that important prior information about kinetic features of a chemical reaction under investigation is ignored during identification. A distinct feature and novelty of this work is a new formulation of the identification problem; the problem was considered as a two-criterion optimization task which allowed to take into account both experimental data on the kinetics of the chemical reaction under investigation and prior information about this reaction. Solution to this problem represents the Pareto set. In order to approximate the Pareto set a modified Adaptive Weighted Sum method was used. One of the purposes of this work is to test the modified AWS method while solving real world two-criterion inverse problems of chemical kinetics. Two-criterion identification problem of kinetics of olefin hydroalumination by halbui2 and clalbui2 was formulated in this work. The algorithms and software which were used are described in this paper. The obtained calculation results were analyzed and discussed. 
Modified method of adaptive weighted sums in the problem of multi-criterion optimization
Engineering Education # 11, November 2013
DOI: 10.7463/1113.0632468
This paper deals with the problem of multi-criterion optimization. It was assumed that the Pareto set is a solution to this problem. A promising approach to solving this problem is the adaptive weighted sum (AWS) method. Just like the classic weighted sum method based on the additive convolution of partial optimality criteria, the adaptive method also is based on the  convolution. But the AWS method also proposes adaptation of weighting coefficients during iterations on the basis of the current location of the search subarea. This method works with meta-models of criterion functions in order to reduce computational costs. Results of our investigations showed that the AWS method provides a high quality Pareto-approximation in case of a convex, although, maybe, unconnected Pareto frontier. For problems with a concave Pareto frontier this method doesn’t always provide sufficient quality of solution or it does but this takes too much time. In some cases the AWS method could provide an unacceptable solution caused by a special method of constraint satisfaction. The purpose of this work is to overcome specified disadvantages of the AWS method. A problem formulation for multi-criterion optimization was presented along with basic approaches to its solving. Several modifications of the ASW method proposed by the authors were considered. A brief description of the developed software implementing the method and its modifications were presented. Performance study of this software was carried out.

Engineering Bulletin # 01, January 2013
Adaptive weighted sum method for solving Pareto-approximation problem
Engineering Education # 06, June 2012
DOI: 10.7463/0612.0423283
The authors consider solving the discrete problem of Pareto set and frontier optimization in the multi-criterion optimization problem. The aim of this work was to examine the efficiency of Adaptive Weighted Sum method (AWS) which was initially developed by J-H. Ryu, S. Kim and H. Wan. Comparing to the original research, the authors used a wider range of multi-criterion benchmark optimization problems. A range of limitations of AWS methodology and usage complexity was found. Modification of the method was proposed to resolve the problems and limitations.
 
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