augmented downhill simplex method (adsm) is introduced here, that is a heuristic combination of downhill simplex method (dsm) with random search algorithm. in fact, dsm is an interpretable nonlinear local optimization method. however, it is a local exploitation algorithm; so, it can be trapped in a local minimum. in contrast, random search is a global exploration, but less efficient. here, rand...

Augmented Downhill Simplex Method (ADSM) is introduced here, that is a heuristic combination of Downhill Simplex Method (DSM) with Random Search algorithm. In fact, DSM is an interpretable nonlinear local optimization method. However, it is a local exploitation algorithm; so, it can be trapped in a local minimum. In contrast, random search is a global exploration, but less efficient. Here, rand...

Block motion estimation can be regarded as a function minimization problem in a finite-dimensional space. Therefore, fast block motion estimation can be achieved by using an efficient function minimization algorithm instead of a predefined search pattern, such as diamond search. Downhill simplex search is an efficient derivative-free function minimization algorithm. In this paper, we proposed a...

The paper deals with testing and evaluation of selected heuristic optimization methods Random Search, Downhill Simplex, Hill Climbing, Tabu Search, Local Search, Simulated Annealing, Evolution Strategy and Differential Evolution. We modified basic methods in such a way that they are applicable for discrete event simulation optimization purposes. The paper is mainly focused on testing Downhill S...

The rough surface inverse scattering problem is approached with a combination of evolutionary strategies and the simplex method. The surface, assumed one-dimensional and perfectly conducting, is represented using spline curves. Starting from rigorously calculated far-field angle-resolved scattered intensity data, we search for the optimum profile using the evolutionary strategies (μ/ρ, λ). Afte...

The downhill simplex method of optimization is a “geometric” method to achieve function minimization. The standard algorithm uses arbitrary values for the deterministic factors that describe the “movement” of the simplex in the merit space. While it is a robust method of optimization, it is relatively slow to converge to local minima. However, its stability and the lack of use of derivates make...

This paper presents two techniques for the design of digital filters with bit-constrained coefficients, the “bit-flipping” algorithm [1] and the Downhill Simplex Method modified to deliver fixedpoint filter coefficients [2]. Both techniques can be applied both to design filters from scratch and to optimise their floating-point equivalents. They are comparatively presented through an example of ...

Purpose: Although transgender people are currently excluded from enlistment and discharged from service based on medical and psychological fitness policies, the current mental and physical health of transgender active-duty U.S. military personnel and veterans is poorly understood. The purpose of the current study was to investigate the military histories, lifetime mental and physical health dia...