Simulated Entropy and Global Minimization
نویسندگان
چکیده
ABSTRACT: Non-linear programming deals with the problem of optimizing an objective function in the presence of equality and inequality constraints. Most of the classical deterministic methods encounter two major problems: (i) the solution obtained is heavily dependent on the starting solution: and (ii) the methods often converge to inferior local optima. This paper examines the relationship between simulated annealing and Shannons entropy with respect to minimization, which introduces for a new subject called simulated entropy (SE). As a consequence, two SE techniques are derived which provide a simple means of seeking the global minimum of constrained minimization problems.
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