Author: "Jiao, Hongwei" / Language: english / Publication Year Range: Last 50 years / Publisher: elsevier b.v. / Topic: computational complexity - Searchworks@Jio Institute Digital Library Search Results

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Start Over Author "Jiao, Hongwei" Topic computational complexity Publication Year Range Last 50 years Language english Publisher elsevier b.v.

Author: Jiao, Hongwei, Wang, Wenjie, and Shang, Youlin
Subjects: *OUTER space, *LOGARITHMIC functions, *COMPUTATIONAL complexity, *GLOBAL optimization
Abstract: This paper presents an outer space branch-reduction-bound algorithm for globally solving generalized affine multiplicative problems (GAMP). For finding the globally optimal solution to the GAMP, we first transform the GAMP into an equivalent problem (EP) by introducing new variables and logarithmic transformation. Next, by utilizing linearization technique of logarithmic function, the affine relaxation problem of the EP can be established for obtaining the lower bound of the optimal value to the EP. Furthermore, several outer space region reduction techniques are also presented for improving the convergence speed of this algorithm. Based on outer space search and branch-and-bound framework, a branch-reduction-bound algorithm is proposed. Finally, we prove the global convergence of the proposed algorithm, and estimate maximum iterations by analyzing its computational complexity. Some experiments are reported to show the feasibility and efficiency of the algorithm. [ABSTRACT FROM AUTHOR]
Published: 2023
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Author: Jiao, Hongwei and Li, Binbin
Subjects: *COMPUTATIONAL complexity, *INDUSTRIAL efficiency, *FRACTIONAL programming, *GLOBAL optimization, *ALGORITHMS, *RECTANGLES, *SEMIDEFINITE programming
Abstract: Based on the image space branch-and-bound scheme, this paper presents a novel algorithm for globally solving the min–max linear fractional programs (MMLFP), which has many applications in management optimization, engineering optimization, economic investment and so on. For finding the global optimal solution of the MMLFP, by leading into new parameter, we firstly transform the MMLFP into an equivalent fractional problem (EFP). Next, by using convex hull and concave hull approximation of bilinear function, we construct the linear relaxation problem (LRP) for computing the lower bound of the global minimum value of the EFP in the image space branch-and-bound algorithm. By subsequently solving a series of linear relaxation problems and refining the initial image space rectangle, the proposed algorithm is globally convergent to the optimum solution of the EFP. In addition, we give the computational complexity analysis of the algorithm based on the exhaustive branching rule. Finally, computational comparisons show better computational performance of the algorithm. [ABSTRACT FROM AUTHOR]
Published: 2022
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