Discrete optimization
Zero duality gap for a class of nonconvex optimization problems
Journal of Optimization Theory and Applications
Success Guarantee of Dual Search in Integer Programming: p-th Power Lagrangian Method
Journal of Global Optimization
Generalized Nonlinear Lagrangian Formulation for Bounded Integer Programming
Journal of Global Optimization
On the existence of duality gaps for mixed integer programming
International Journal of Systems Science
Comment on "A nonlinear Lagrangian dual for integer programming"
Operations Research Letters
A nonlinear Lagrangian dual for integer programming
Operations Research Letters
On the resolution of the system of fuzzy Diophantine equations
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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A p-norm surrogate constraint method is proposed for integer programming. A single surrogate constraint can be always constructed using a p-norm such that the feasible sets in a surrogate relaxation and the primal problem match exactly. The p-norm surrogate constraint method is thus guaranteed to succeed in identifying an optimal solution of the primal problem with zero duality gap. The existence of a saddle point is proven for integer programming problems.