Pareto Optimization as the Basic for Selecting Robotic Mechanic Assembly Technologies  

作　　者：Valerii Kyrylovych Dragoljub Tanovic Dmytro Melnychuk Liudmyla Mohelnytska Petro Melnychuk Valery Yanovsky Valerii Kyrylovych;Dragoljub Tanovic;Dmytro Melnychuk;Liudmyla Mohelnytska;Petro Melnychuk;Valery Yanovsky(Faculty of Computer-Integrated Technologies, Mechatronics and Robotics, Zhytomyr Polytechnic State University, Zhytomyr, Ukraine;Faculty of Mechanical Engineering, University of Belgrade, Belgrade, Serbia)

机构地区：[1]Faculty of Computer-Integrated Technologies, Mechatronics and Robotics, Zhytomyr Polytechnic State University, Zhytomyr, Ukraine [2]Faculty of Mechanical Engineering, University of Belgrade, Belgrade, Serbia

出　　处：《Applied Mathematics》2024年第6期421-439,共19页应用数学（英文）

摘　　要：The task of selecting robotic mechanic assembly technologies (RMAT) is considered as a multi-criteria optimization task, which in this formulation is solved on the set of previously obtained solutions regarding the selection of RMAT. The purpose of the paper is to increase the efficiency of technological preparation of robotic mechanical assembly production of machine and instrument engineering due to a new approach to the selection of RMAT using Pareto optimization and the peculiarities of the selection task formulation. The novelty consists in the further development of a science-based approach to solving multi-criteria selection task, based on the first proposed formalisms of the specified process, which reflect the peculiarities of the selection task formulation, its meaningful essence and the content of the Pareto optimization method. The practical value of the research lies in the proposed engineering-acceptable approach to solving applied multi-criteria selection tasks on the example of RMAT selection, which is invariant to the statement of the selection task, the dimension of the task, and its meaningful essence. The methods of discrete optimization, fuzzy multi-criteria selection of alternatives, and the Pareto optimization method were used for the research. The main results of this work consist of the development of formalisms and the demonstration of the efficiency of the proposed approach for the applied task of RMAT selection. The peculiarity of the developed approach is the combination of Pareto optimization, performed on a discrete set of local criteria. Directions for further research are presented.The task of selecting robotic mechanic assembly technologies (RMAT) is considered as a multi-criteria optimization task, which in this formulation is solved on the set of previously obtained solutions regarding the selection of RMAT. The purpose of the paper is to increase the efficiency of technological preparation of robotic mechanical assembly production of machine and instrument engineering due to a new approach to the selection of RMAT using Pareto optimization and the peculiarities of the selection task formulation. The novelty consists in the further development of a science-based approach to solving multi-criteria selection task, based on the first proposed formalisms of the specified process, which reflect the peculiarities of the selection task formulation, its meaningful essence and the content of the Pareto optimization method. The practical value of the research lies in the proposed engineering-acceptable approach to solving applied multi-criteria selection tasks on the example of RMAT selection, which is invariant to the statement of the selection task, the dimension of the task, and its meaningful essence. The methods of discrete optimization, fuzzy multi-criteria selection of alternatives, and the Pareto optimization method were used for the research. The main results of this work consist of the development of formalisms and the demonstration of the efficiency of the proposed approach for the applied task of RMAT selection. The peculiarity of the developed approach is the combination of Pareto optimization, performed on a discrete set of local criteria. Directions for further research are presented.

关 键 词：Multicriteria Optimization Efficiency Fuzzy Multicriteria Selection of Alternatives 

分 类 号：TP1[自动化与计算机技术—控制理论与控制工程]