Multiple Minima Problem in Protein Folding: αBB Global Optimization Approach

2012 ◽  
Keyword(s):  
Protein Folding ◽  
Global Optimization ◽  
Optimization Approach ◽  
Multiple Minima

scholarly journals Contaminant source localization via Bayesian global optimization

2017 ◽  
Author(s):  
Guillaume Pirot ◽  
Tipaluck Krityakierne ◽  
David Ginsbourger ◽  
Philippe Renard
Keyword(s):  
Global Optimization ◽  
Process Model ◽  
Bayesian Optimization ◽  
Expected Improvement ◽  
Optimization Approach ◽  
Objective Functions ◽  
Contaminant Source ◽  
Multiple Minima ◽  
Improvement Criterion ◽  
Linear Objective Functions

Abstract. A Bayesian optimization approach to localize a contaminant source is proposed. The localization problem is illustrated with two 2D synthetic cases which display sharp transmissivity contrasts and specific connectivity patterns. These cases generate highly non-linear objective functions that present multiple local minima. A derivative-free global optimization algorithm relying on a Gaussian Process model and on the Expected Improvement criterion is used to efficiently localize the minimum of the objective function which identifies the contaminant source. In addition, the generated objective functions are made available as a benchmark to further allow the comparison of optimization algorithms on functions characterized by multiple minima and inspired by concrete field applications.

scholarly journals A Global Optimization Approach to Solve Multi-Aircraft Routing Problems

2010 ◽  
pp. 237-259
Author(s):  
S.P. Wilson ◽  
M.C. Bartholomew-Biggs ◽  
S.C. Parkhurst
Keyword(s):  
Global Optimization ◽  
Real Life ◽  
Two Dimensions ◽  
Numerical Results ◽  
Solution Technique ◽  
Optimization Approach ◽  
Routing Problem ◽  
Aircraft Routing ◽  
Optimization Calculation ◽  
Multiple Routes

This chapter describes the formulation and solution of a multi-aircraft routing problem which is posed as a global optimization calculation. The chapter extends previous work (involving a single aircraft using two dimensions) which established that the algorithm DIRECT is a suitable solution technique. The present work considers a number of ways of dealing with multiple routes using different problem decompositions. A further enhancement is the introduction of altitude to the problems so that full threedimensional routes can be produced. Illustrative numerical results are presented involving up to three aircraft and including examples which feature routes over real-life terrain data.

scholarly journals Metabolite discovery through global annotation of untargeted metabolomics data

2021 ◽  
Author(s):  
Li Chen ◽  
Wenyun Lu ◽  
Lin Wang ◽  
Xi Xing ◽  
Xin Teng ◽  
...  
Keyword(s):  
Global Optimization ◽  
High Resolution Mass Spectrometry ◽  
Mass Difference ◽  
Untargeted Metabolomics ◽  
Global Network ◽  
Optimization Approach ◽  
Metabolomics Data ◽  
Isotope Tracer ◽  
Powerful Approach ◽  
Fragmentation Patterns

AbstractA primary goal of metabolomics is to identify all biologically important metabolites. One powerful approach is liquid chromatography-high resolution mass spectrometry (LC-MS), yet most LC-MS peaks remain unidentified. Here, we present a global network optimization approach, NetID, to annotate untargeted LC-MS metabolomics data. We consider all experimentally observed ion peaks together, and assign annotations to all of them simultaneously so as to maximize a score that considers properties of peaks (known masses, retention times, MS/MS fragmentation patterns) as well network constraints that arise based on mass difference between peaks. Global optimization results in accurate peak assignment and trackable peak-peak relationships. Applying this approach to yeast and mouse data, we identify a half-dozen novel metabolites, including thiamine and taurine derivatives. Isotope tracer studies indicate active flux through these metabolites. Thus, NetID applies existing metabolomic knowledge and global optimization to annotate untargeted metabolomics data, revealing novel metabolites.

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