TY - JOUR
T1 - Double well potential function and its optimization in the n-dimensional real space - Part I
AU - Fang, Shü Cherng
AU - Gao, David Y.
AU - Lin, Gang Xüan
AU - Sheü, Rüey Lin
AU - Xing, Wenxün
N1 - Funding Information:
This research was undertaken while Y. Xia visited the Na tional Cheng Kung University, Tainan, Taiwan. S-C Fang's research has been supported by US ARO Grant # W911NF-15-1-0223. R-L Sheu's research work was sponsored partially by Taiwan NSC 98-2115-M-006-010-MY2 and by National Center for Theoretic Sciences (The southern branch). Y. Xia's research work was supported by National Natural Science Foundation of China under grants 11471325 and 11571029, and by fundamental research funds for the Central Universities un der grant YWF-16-BJ-Y-11. W. Xing's research work was supported by NSFC No. 11171177.
PY - 2017/7/1
Y1 - 2017/7/1
N2 - A special type of multi-variate polynomial of degree 4, called the double well potential function, is studied. It is derived from a discrete approx imation of the generalized Ginzburg-Landau functional, and we are interested in understanding its global minimum solution and all local non-global points. The main difficulty for the model is due to its non-convexity. In Part I of the paper, we first characterize the global minimum solution set, whereas the study for local non-global optimal solutions is left for Part II. We show that, the dual of the Lagrange dual of the double well potential problem is a linearly constrained convex minimization problem, which, under a designated nonlin ear transformation, can be equivalently mapped to a portion of the original double well potential function containing the global minimum. In other words, solving the global minimum of the double well potential function is essentially a convex minimization problem, despite of its non-convex nature. Numerical examples are provided to illustrate the important features of the problem and the mapping in between.
AB - A special type of multi-variate polynomial of degree 4, called the double well potential function, is studied. It is derived from a discrete approx imation of the generalized Ginzburg-Landau functional, and we are interested in understanding its global minimum solution and all local non-global points. The main difficulty for the model is due to its non-convexity. In Part I of the paper, we first characterize the global minimum solution set, whereas the study for local non-global optimal solutions is left for Part II. We show that, the dual of the Lagrange dual of the double well potential problem is a linearly constrained convex minimization problem, which, under a designated nonlin ear transformation, can be equivalently mapped to a portion of the original double well potential function containing the global minimum. In other words, solving the global minimum of the double well potential function is essentially a convex minimization problem, despite of its non-convex nature. Numerical examples are provided to illustrate the important features of the problem and the mapping in between.
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U2 - 10.3934/jimo.2016073
DO - 10.3934/jimo.2016073
M3 - Article
AN - SCOPUS:85021773720
SN - 1547-5816
VL - 13
SP - 1291
EP - 1305
JO - Journal of Industrial and Management Optimization
JF - Journal of Industrial and Management Optimization
IS - 3
ER -