Journal
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
Volume 223, Issue 1, Pages 356-373Publisher
ELSEVIER
DOI: 10.1016/j.cam.2008.01.023
Keywords
Box constrained nonlinear integer programming; Convexized method; Discrete local minimizer; Convergence
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Funding
- National Natural Science Foundation of China [60773126, 10301009]
- Natural Science Foundation of Fujian Province [2006J0030]
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In this paper, we consider the box constrained nonlinear integer programming problem. We present an auxiliary function, which has the same discrete global minimizers as the problem. The minimization of the function using a discrete local search method can escape successfully from previously converged discrete local minimizers by taking increasing values of a parameter. We propose an algorithm to find a global minimizer of the box constrained nonlinear integer programming problem. The algorithm minimizes the auxiliary function from random initial points. We prove that the algorithm can converge asymptotically with probability one. Numerical experiments on a set of test problems show that the algorithm is efficient and robust. (c) 2008 Elsevier B.V. All rights reserved.
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