Scatter Search and Local NLP Solvers: A Multistart Framework for Global Optimization

By Zsolt Ugray, L. Lasdon, John C. Plummer, Fred W. Glover, J. Kelly, Rafael Martí. 2007

728 citations recorded by the source corpus.

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A Stochastic Radial Basis Function Method for the Global Optimization of Expensive Functions (2007, methodology): “Other examples are multistart frameworks for local optimization such as OQNLP (Ugray et al. 2006), which uses scatter search to select starting points for any gradient-based solver.”
MINLP Solver Software (2011, methodology): “Finally, OQNLP applies a randomized approach by sampling starting points and fixations of integer variables for the solution of NLP subproblems.”
Robust stochastic optimization for reservoir operation (2015, methodology): “This set could be obtained by employing multistart optimization procedure [Ugray et al., 2007] that starts the local solver from a variety of starting points (generally the starting points are random) which converge to different solutions.”
Automated Algorithm Selection: Survey and Perspectives (2018, methodology): “The commercial solver OptQuest/NLP (Pál, 2013; Ugray et al., 2007) was also included.”
Bringing a Blurry Frame Alive at High Frame-Rate With an Event Camera (2018, methodology): “This single-variable minimization problem can be solved by the nonlinear least-squares method [19], Scatter-search[36] or Fibonacci search [6].”