Abstract
The watchdog technique is an extension to iterative optimization algorithms that use line searches. The purpose is to allow some iterations to choose step-lengths that are much longer than those that would be allowed normally by the line search objective function. Reasons for using the technique are that it can give large gains in efficiency when a sequence of steps has to follow a curved constraint boundary, and it provides some highly useful algorithms with a Q-superlinear rate of convergence. The watchdog technique is described and discussed, and some global and Q-superlinear convergence properties are proved.
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References
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© 1982 The Mathematical Programming Society, Inc.
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Chamberlain, R.M., Powell, M.J.D., Lemarechal, C., Pedersen, H.C. (1982). The watchdog technique for forcing convergence in algorithms for constrained optimization. In: Buckley, A.G., Goffin, J.L. (eds) Algorithms for Constrained Minimization of Smooth Nonlinear Functions. Mathematical Programming Studies, vol 16. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0120945
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DOI: https://doi.org/10.1007/BFb0120945
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