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Regional division and reduction algorithm for minimizing the sum of linear fractional functions.

Pei-Ping ShenTing Lu
Published in: Journal of inequalities and applications (2018)
This paper presents a practicable regional division and cut algorithm for minimizing the sum of linear fractional functions over a polyhedron. In the algorithm, by using an equivalent problem (P) of the original problem, the proposed division operation generalizes the usual standard bisection, and the deleting and reduction operations can cut away a large part of the current investigated region in which the global optimal solution of (P) does not exist. The main computation involves solving a sequence of univariate equations with strict monotonicity. The proposed algorithm is convergent to the global minimum through the successive refinement of the solutions of a series of univariate equations. Numerical results are given to show the feasibility and effectiveness of the proposed algorithm.
Keyphrases
  • machine learning
  • deep learning
  • neural network
  • randomized controlled trial
  • systematic review