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Showing 1 to 5 of 5 for “"Variable Target Value Method"”.
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Nondifferentiable Optimization of Lagrangian Dual Formulations for Linear Programs with Recovery of Primal Solutions
… which simplex as well as interior point based methods can tend to be ineffective. In contrast, Lagrangian relaxation or dual formulations, when applied in concert with suitable primal recovery strategies, have the potential for providing quick bounds as well as enabling useful branching …
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Limited Memory Space Dilation and Reduction Algorithms
… memory updates for differentiable quasi-Newton methods. This well known r-algorithm, which employs a space dilation strategy in the direction of the difference between two successive subgradients, is recognized as being one of the most effective procedures for solving nondifferentiable …
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Nondifferentiable optimization algorithms with application to solving Lagrangian dual problems
… Lagrangian duality, penalty function methods, and minimax problems. The importance and necessity of having effective solution methods for NDO problems has long been recognized by many scientists and engineers. However, the practical use of NDO techniques has been somewhat limited, …
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Algorithmic Approaches for Solving the Euclidean Distance Location and Location-Allocation Problems
… are proposed. The subgradient deflection method considered is the Average Direction Strategy (ADS) imbedded within the Variable Target Value Method (VTVM). The generation of two types of subgradients that are employed in conjunction with ADS are investigated. The first type is a simple …
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Tight Flow-Based Formulations for the Asymmetric Traveling Salesman Problem and Their Applications to some Scheduling Problems
… advantage of their relaxations (of integer variables, thereby, resulting in linear programs) to effectively solve large-size problems. In view of our objective, it is essential to have a formulation that is amenable to the development of an effective solution procedure for the underlying …