Abstract
Image space analysis has proved to be instrumental in unifying several theories, apparently disjoint from each other. With reference to constraint qualifications/regularity conditions in optimization, such an analysis has been recently introduced by Moldovan and Pellegrini. Based on this result, the present paper is a preliminary part of a work, which aims at exploiting the image space analysis to establish a general regularity condition for constrained extremum problems. The present part deals with scalar constrained extremum problems in a Euclidean space. The vector case as well as the case of infinite-dimensional image will be the subject of a subsequent part.
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Notes
This condition has been proposed in Comment (O) of [19].
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Acknowledgements
The author is grateful to Professor Franco Giannessi and Professor Letizia Pellegrini for their constructive comments on this paper and their great help when this work was carried out during a stay of the author in the Department of Mathematics, University of Pisa. The author expresses his gratitude to the anonymous referees for their valuable comments and suggestions, which help to improve the paper. This research was supported by China Scholarship Council, the National Natural Science Foundation of China (Grants 11601437, 11526165) the Basic and Advanced Research of CQ CSTC (Grant cstc2015jcyja00038), the Scientific and Technological Research Program of Chongqing Municipal Education Commission (Grant KJ1501503) and the Chongqing Research Program of Basic Research and Frontier Technology (cstc2016jcyjA0270).
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Zhu, S. Constrained Extremum Problems, Regularity Conditions and Image Space Analysis. Part I: The Scalar Finite-Dimensional Case. J Optim Theory Appl 177, 770–787 (2018). https://doi.org/10.1007/s10957-018-1216-6
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DOI: https://doi.org/10.1007/s10957-018-1216-6