Journal of Applied Science and Engineering A
https://mongoliajol.info/index.php/JASE-A
<p>published by the School of Applied Sciences, Mongolian University of Science and Technology.</p> <p><strong>Abstracting and indexing in <a title="Google Scholar" href="https://scholar.google.com/" target="_blank" rel="noopener">Google Scholar</a>, <a title="Mongolian Journal of Geography and Geoecology" href="https://app.dimensions.ai/" target="_blank" rel="noopener">Dimensions,</a> and <a title="EBSCO Discovery service" href="https://www.ebscohost.com/discovery" target="_blank" rel="noopener">EBSCO Discovery service</a></strong></p>Mongolian University of Science and Technologyen-USJournal of Applied Science and Engineering A2664-2026<p>Copyright on any research article in the <strong>Journal of Applied Science and Engineering A</strong> is retained by the author(s).</p> <p>The authors grant the <strong>Journal of Applied Science and Engineering A</strong> a license to publish the article and identify itself as the original publisher.</p> <p><a href="http://creativecommons.org/licenses/by/4.0/" rel="license"><img src="https://i.creativecommons.org/l/by/4.0/88x31.png" alt="Creative Commons Licence" /></a><br />Articles in the <strong>Journal of Applied Science and Engineering A</strong> are Open Access articles published under a <a href="http://creativecommons.org/licenses/by/4.0/" rel="license">Creative Commons Attribution 4.0 International License</a> CC BY.</p> <p>This license permits use, distribution and reproduction in any medium, provided the original work is properly cited.</p> <p> </p>Multiplicative Optimal Control Problem
https://mongoliajol.info/index.php/JASE-A/article/view/2684
<p>In this paper, we consider a multiplicative optimal control problem subject to a system of linear differential equation.It has been shown that product of two concave functions defined positively over a feasible set is quasiconcave. It allows us to consider the original problem from a view point of quasiconvex maximization theory and algorithm. Global optimality conditions use level set of the objective function and convex programming as subproblem. The objective function is product of two concave functions. We consider minimization of the objective functional. The problem is nonconvex optimal control and application of Pontriyagin’s principle does not always guarantee finding a global optimal control. Based on global optimality conditions, we develop an algorithm for solving the minimization problem globally.</p>Enkhbat RentsenBayartugs TamjavUlziibayar Vandandoo
Copyright (c) 2023 Enkhbat Rentsen, Bayartugs Tamjav, Ulziibayar Vandandoo,
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2023-07-032023-07-03411710.5564/jasea.v4i1.2684