Global optimization

Known as: Global minimization, Global optimisation, Local minimization 
Global optimization is a branch of applied mathematics and numerical analysis that deals with the global optimization of a function or a set of… (More)
Wikipedia

Topic mentions per year

Topic mentions per year

1964-2017
0500100019642017

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2007
Highly Cited
2007
The successful application of a conceptual rainfall-runoff (CRR) model depends on how well it is calibrated. Despite the… (More)
  • figure 1
  • figure 2
  • figure 3
  • figure 6
  • figure 5
Is this relevant?
Highly Cited
2006
Highly Cited
2006
This paper presents a variant of particle swarm optimizers (PSOs) that we call the comprehensive learning particle swarm… (More)
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Is this relevant?
Highly Cited
2004
Highly Cited
2004
  • E. R
  • 2004
We show how interval analysis can be used to compute the minimum value of a twice continuously differentiable function of one… (More)
Is this relevant?
Highly Cited
2001
Highly Cited
2001
We consider the problem of finding the unconstrained global minimum of a realvalued polynomial p(x) : Rn → R, as well as the… (More)
Is this relevant?
Highly Cited
1999
Highly Cited
1999
Inspired by a method by Jones et al. (1993), we present a global optimization algorithm based on multilevel coordinate search. It… (More)
  • figure 1
  • figure 2
  • table I
  • table II
  • table III
Is this relevant?
Highly Cited
1998
Highly Cited
1998
In many engineering optimization problems, the number of function evaluations is severely limited by time or cost. These problems… (More)
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Is this relevant?
Highly Cited
1998
Highly Cited
1998
The two dominant schemes for rule learning C and RIPPER both operate in two stages First they induce an initial rule set and then… (More)
Is this relevant?
Highly Cited
1997
Highly Cited
1997
A new heuristic approach for minimizing possibly nonlinear and non-differentiable continuous space functions is presented. By… (More)
  • figure 1
  • figure 2
  • table 1
  • table 2
  • table 3
Is this relevant?
Highly Cited
1996
Highly Cited
1996
A new heuristic approach for minimizing possibly nonlinear and non differentiable continuous space functions is presented. By… (More)
  • figure 2
  • table I
Is this relevant?
Highly Cited
1990
Highly Cited
1990
Many statistical methods rely on numerical optimization to estimate a model’s parameters. Unfortunately, conventional algorithms… (More)
  • table 1
  • table 2
  • table 3
  • table 4
  • table 5
Is this relevant?