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Global Optimality Conditions and Near-Perfect Optimization in Coding

Authors: Xiaofei Huang;

Global Optimality Conditions and Near-Perfect Optimization in Coding

Abstract

Finding ways of recognizing global optimum is the very fundamental, unsolved problem in existing optimization theories. We can not establish a true theory of optimization without it. Also, it is very hard to construct effective algorithms for finding global optimum. This paper presented a new optimization principle, called cooperative optimization, for solving this extremely important problem in optimization theory. A number of global optimality conditions are provided in a general form. The application of cooperative optimization in coding yields near-perfect results in finding global optima, significantly better than the most powerful optimization algorithm ever found so far.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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