Stochastic global optimization methods. part 1: clustering methods
Mathematical Programming: Series A and B
Stochastic global optimization methods. part 11: multi level methods
Mathematical Programming: Series A and B
Discrete optimization
A filled function method for finding a global minimizer of a function of several variables
Mathematical Programming: Series A and B
Optimal pacing of trains in freight railroads: model formulation and solution
Operations Research
Lagrangian decomposition for integer nonlinear programming with linear constraints
Mathematical Programming: Series A and B
Solving mixed integer nonlinear programs by outer approximation
Mathematical Programming: Series A and B
Zero duality gap for a class of nonconvex optimization problems
Journal of Optimization Theory and Applications
Smart greedy procedure for solving a nOnlinear knapsack class of reliability optimization problems
Mathematical and Computer Modelling: An International Journal
Zero duality gap in integer programming: P-norm surrogate constraint method
Operations Research Letters
Discrete Filled Function Method for Discrete Global Optimization
Computational Optimization and Applications
Generalized Nonlinear Lagrangian Formulation for Bounded Integer Programming
Journal of Global Optimization
Discrete global descent method for discrete global optimization and nonlinear integer programming
Journal of Global Optimization
Journal of Global Optimization
Convergent Lagrangian and domain cut method for nonlinear knapsack problems
Computational Optimization and Applications
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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Although the Lagrangian method is a powerful dual search approach in integer programming, it often fails to identify an optimal solution of the primal problem. The p-th power Lagrangian method developed in this paper offers a success guarantee for the dual search in generating an optimal solution of the primal integer programming problem in an equivalent setting via two key transformations. One other prominent feature of the p-th power Lagrangian method is that the dual search only involves a one-dimensional search within [0,1]. Some potential applications of the method as well as the issue of its implementation are discussed.