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 paper addresses tlie design of tlie polyphase IIR filters based on the “’-order single-coefficient allpass sub-filters in the constraint coefficient space using the Constraint Dowdiill Simplex Algorithm. Incorporating the bit-flipping algorithm into its core engine allowed the optitilisation routine to converge to better target designs without affecting tlie Iiigli speed of tlie original al...

The evolutionary annealing-simplex algorithm is a probabilistic heuristic global optimisation technique that joins ideas from different methodological approaches, enhancing them with some original elements. The main concept is based on a controlled random search scheme, where a generalised downhill simplex methodology is coupled with a simulated annealing procedure. The algorithm combines the r...

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...

In water resources optimization problems, the objective function usually presumes to first run a simulation model and then evaluate its outputs. However, long simulation times may pose significant barriers to the procedure. Often, to obtain a solution within a reasonable time, the user has to substantially restrict the allowable number of function evaluations, thus terminating the search much e...

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 ...