An outer-approximation algorithm for a class of mixed-integer nonlinear programs
Mathematical Programming: Series A and B
Integer and combinatorial optimization
Integer and combinatorial optimization
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Computers and Operations Research
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ACM Transactions on Mathematical Software (TOMS)
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Computational Optimization and Applications
MINLPLib--A Collection of Test Models for Mixed-Integer Nonlinear Programming
INFORMS Journal on Computing
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Mathematical Programming: Series A and B
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Mathematical Programming: Series A and B
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SIAM Journal on Optimization
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Journal of Global Optimization
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Journal of Computational and Applied Mathematics
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Journal of Computational and Applied Mathematics
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ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part I
Checking local optimality in constrained quadratic programming is NP-hard
Operations Research Letters
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We consider in this paper the nonconvex mixed-integer nonlinear programming problem. We present a mixed local search method to find a local minimizer of an unconstrained nonconvex mixed-integer nonlinear programming problem. Then an auxiliary function which has the same global minimizers and the same global minimal value as the original problem is constructed. Minimization of the auxiliary function using our local search method can escape successfully from previously converged local minimizers by taking increasing values of parameters. For the constrained nonconvex mixed-integer nonlinear programming problem, we develop a penalty based method to convert the problem into an unconstrained one, and then use the above method to solve the later problem. Numerical experiments and comparisons on a set of MINLP benchmark problems show the effectiveness of the proposed algorithm.