1. An outcome space algorithm for solving general linear multiplicative programming.
- Author
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Zhang, Yanzhen and Shen, Peiping
- Subjects
- *
LINEAR programming , *COMPUTATIONAL complexity , *ALGORITHMS - Abstract
The following article presents and corroborates an outcome space branch-and-bound algorithm for solving the general linear multiplicative programming problem (GLMPP). In this new algorithm, GLMPP is transformed into its equivalent problem by introducing auxiliary variables. To compute the tight upper bound for the optimal value of GLMPP, the linear relaxation programming problem is assembled by using bound and hull linear approximations. Furthermore, the global convergence and computational complexity of the algorithm are demonstrated. Finally, the soundness and advantage of the proposed algorithm are validated by solving a demonstrative linear multiplicative problem. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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