In this paper, a new algorithm, named as Nash-lambda algorithm by merging Nash equilibrium solution and the lambda algorithm, is proposed. The lambda algorithm, a new global optimization algorithm, is created by imitating ancient Chinese human body system model, which has already demonstrated its simplicity in searching scheme, codes and efficiency in computation comparing to the genetic algorithm. The noncorporative game environments determine the optimization problems which are different from those of the traditional safety and reliability optimizations because of the engagement of the Nash equilibrium for seeking the best strategy. The lambda algorithm serves the searching the Nash equilibrium solution efficiently. In other worlds, the Nash-lambda algorithm is just developed to address the optimization problems of the multiple objective functions representing non-corporative players’ interests.
In this paper, a new global optimization algorithm by imitating ancient Chinese human body system model, named as lambda algorithm, is introduced. The lambda algorithm utilizes five-element multi-segment string to represent the n-dimensional Euclidean point and hence the string based operation rules for expansion, comparison and sorting candidate strings. The algorithm enjoys the simplest mathematical operations but generates highest searching speed and accuracy. We furthermore explore to merge the lambda algorithm with maximum likelihood procedure for creating a non-derivative scheme – likelihood- lambda procedure. A illustrative example is given.
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