Under construction...
Only a few algorithms are listed right now. More and more algorithms are to be added later on.

(1) LDSE: Low dimensional simplex evolution
        An algorithm for general global optimization

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LDSE  is a simple but very powerful stochastic optimizer for global optimization. It is a hybrid of downhill simplex and evolutionary algorithm (EA).  Different from other hybrid EA, the simplex operators therein are modified according to EA properties, and used selectively and conditionally. Such that LDSE can keep a good balance between local exploitation and global exploration. LDSE has been applied to solve many scientific/engineering problems, and proved very efficient and robust. 

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(2) LDSEE: LDSE Extension (Pronounced as 'LDC')
      An algorithm for expensive global optimization

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LDSEE is a metamodel-assisted evolutionary algorithm for expensive optimization problems. LDSEE unpacks LDSE and repacks it with model approximation, tabu search and simulated annealing techniques. Such that it can keep a good balance between model approximation and global search. It is inherently parallel and self contained. This renders it very easy to use. Numerical results show that LDSEE is a competitive alternative for expensive optimization problems.

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