Two Algorithms for Solving Unconstrained Global Optimization by Auxiliary Function Method

In this paper, we present two algorithms that are designed to solve unconstrained global optimization problems. The first algorithm is introduced for resolving unconstrained optimization problems by dividing a multidimensional problem into partitions of a one-dimensional problem and subsequently ide...

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Veröffentlicht in:Tikrit Journal of Pure Science Jg. 29; H. 3; S. 84 - 89
Hauptverfasser: Ibrahem, Shehab Ahmed, Isam Haider Halil, Suaad Madhat Abdullah
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Tikrit University 25.06.2024
Schlagworte:
Auxiliary function
conjugate gradient methods, unconstrained optimization, Nonlinear programming
Global optimization
Smoothing technique
ISSN:1813-1662, 2415-1726
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Zusammenfassung:In this paper, we present two algorithms that are designed to solve unconstrained global optimization problems. The first algorithm is introduced for resolving unconstrained optimization problems by dividing a multidimensional problem into partitions of a one-dimensional problem and subsequently identifying a global minimizer for each partition by utilizing an auxiliary function and then using it to find the global minimizer of a multidimensional problem. In the second algorithm, the same auxiliary function is used to find a global minimizer of the same multidimensional problem without partitioning it. Finally, we apply these algorithms to common test problems and compare them to each other to show the efficiency of the algorithms
ISSN:1813-1662
2415-1726
DOI:10.25130/tjps.v29i3.1604