A stochastic augmented Lagrangian equality constrained-based algorithm for global optimization

By Rocha, A.M.A.C.; Fernandes, E.M.G.P.

AIP Conference Proceedings



This paper presents a numerical study of a stochastic augmented Lagrangian algorithm to solve continuous constrained global optimization problems. The algorithm approximately solves a sequence of bound constrained subproblems whose objective function penalizes equality and inequality constraints violation and depends on the Lagrange multiplier vectors and a penalty parameter. Each subproblem is solved by a population-based method that uses an electromagnetism-like mechanism to move points towards optimality. A comparison with another stochastic technique is also reported.


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