Minimization methods for non-differentiable functions
Minimization methods for non-differentiable functions
Testing Unconstrained Optimization Software
ACM Transactions on Mathematical Software (TOMS)
Lagrangian bounds for just-in-time job-shop scheduling
Computers and Operations Research
The prize collecting Steiner tree problem: models and Lagrangian dual optimization approaches
Computational Optimization and Applications
Robust l∞-stability of systems with repeated perturbations: a case study
ICS'05 Proceedings of the 9th WSEAS International Conference on Systems
A hybrid differential evolution method for dynamic economic dispatch with valve-point effects
Expert Systems with Applications: An International Journal
Design of robust stable controls for nonlinear objects
Automation and Remote Control
New Exact Algorithms for One-Machine Earliness-Tardiness Scheduling
INFORMS Journal on Computing
A DFO technique to calibrate queueing models
Computers and Operations Research
High-level approach to modeling of observed system behavior
Performance Evaluation
Exact algorithms for OWA-optimization in multiobjective spanning tree problems
Computers and Operations Research
Invariant sets for families of linear and nonlinear discrete systems with bounded disturbances
Automation and Remote Control
A hybrid computer-aided linkage design system for tracing open and closed planar curves
Computer-Aided Design
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Here we introduce a new implementation of well-known Shor'sr-algorithm with space dilations along the difference of twosuccessive (sub)gradients for minimization of a nonlinear (non-smooth)function (N.Z. Shor, Minimization methods for Non-DifferentiableFunctions, Springer-Verlag: Berlin, 1985. Springer Seriesin Computational Mathematics, vol. 3).The modifications made to Shor's algorithm areheuristic. They mostly concern the termination criteria and the line searchstrategy. A large number of test runs indicate that this implementationis very robust, efficient and accurate. We hope that this implementationof Shor's r-algorithm will prove to be useful for solvinga wide class of non-smooth optimization problems.