The Nelder-Mead simplex method is an optimization routine that works well with irregular objective functions. For a function of <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$n$$</EquationSource> </InlineEquation> parameters, it compares the objective function at the <InlineEquation ID="IEq2"> <EquationSource Format="TEX">$$n+1$$</EquationSource> </InlineEquation> vertices of a simplex and updates the worst vertex through simplex search steps. However, a...</equationsource></inlineequation></equationsource></inlineequation>

In this work we propose a highly optimized version of a simulated annealing (SA) algorithm adapted to the more recently developed graphic processor units (GPUs). The programming has been carried out with compute unified device architecture (CUDA) toolkit, specially designed for Nvidia GPUs. For...

Multidimensional scaling is a technique for exploratory analysis of multidimensional data. The essential part of the technique is minimization of a multimodal function with unfavorable properties like invariants and non-differentiability. Recently a branch and bound algorithm for...

In this paper, we consider two decomposition schemes for the graph theoretical description of the axial Multidimensional Assignment Problem (MAP). The problem is defined as finding n disjoint cliques of size m with minimum total cost in K <Subscript> m×n </Subscript>, which is an m-partite graph with n elements per...</subscript>