An efficient image space branch-reduction-bound algorithm to globally solve generalized fractional programming problems for large-scale real applications
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Publication:6582024
DOI10.1016/j.cam.2024.116070MaRDI QIDQ6582024
Publication date: 1 August 2024
Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)
computational complexityglobal optimizationgeneralized fractional programming problemsbranch-reduction-boundtwo-phase relaxation technique
Cites Work
- A practicable branch and bound algorithm for sum of linear ratios problem
- Augmented Lagrange primal-dual approach for generalized fractional programming problems
- Range division and compression algorithm for quadratically constrained sum of quadratic ratios
- Approximation of linear fractional-multiplicative problems
- A new linearization method for generalized linear multiplicative programming
- On the global optimization of sums of linear fractional functions over a convex set
- Regional division and reduction algorithm for minimizing the sum of linear fractional functions
- Generating the efficient set of multiobjective integer linear plus linear fractional programming problems
- Linearization method for a class of multiplicative programming with exponent
- Global optimization of generalized linear fractional programming with nonlinear constraints
- A new rectangle branch-and-pruning approach for generalized geometric programming
- A simplicial branch and bound duality-bounds algorithm for the linear sum-of-ratios problem
- Global optimization of multiplicative programs
- A unified monotonic approach to generalized linear fractional programming
- Global optimization of signomial geometric programming using linear relaxation.
- Range division and linearization algorithm for a class of linear ratios optimization problems
- Linearization method of global optimization for generalized geometric programming
- A new two-level linear relaxed bound method for geometric programming problems
- Generalized fractional programming and cutting plane algorithms
- An interior-point method for generalized linear-fractional programming
- Underestimation functions for a rank-two partitioning method
- Outer space branch-reduction-bound algorithm for solving generalized affine multiplicative problems
- Effective algorithm for solving the generalized linear multiplicative problem with generalized polynomial constraints
- Solving a class of generalized fractional programming problems using the feasibility of linear programs
- A global optimization algorithm for linear fractional programming
- Global optimization for sum of generalized fractional functions
- Global optimization algorithm for a generalized linear multiplicative programming
- Global optimization method for maximizing the sum of difference of convex functions ratios over nonconvex region
- A branch and bound algorithm for globally solving a class of nonconvex programming problems
- A branch and bound algorithm to globally solve the sum of several linear ratios
- A deterministic global optimization algorithm for generalized geometric programming
- Global algorithm for a class of multiplicative programs using piecewise linear approximation technique
- An efficient algorithm and complexity result for solving the sum of general affine ratios problem
- A new solution method for a class of large dimension rank-two nonconvex programs
- Image space branch-reduction-bound algorithm for globally minimizing a class of multiplicative problems
- Two-level linear relaxation method for generalized linear fractional programming
- An efficient spatial branch-and-bound algorithm using an adaptive branching rule for linear multiplicative programming
- A new deterministic global computing algorithm for solving a kind of linear fractional programming
- A potential practical algorithm for minimizing the sum of affine fractional functions
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