Titlebook: Entropy Optimization and Mathematical Programming; S.-C. Fang,J. R. Rajasekera,H.-S. J. Tsao Book 1997 Springer Science+Business Media New

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Book 1997y Optimizationand. .Mathematical Programming. offers perspectives that meetthe needs of diverse .user communities. so that the users canapply .entropy. .optimization techniques. with completecomfort and ease. With this consideration, the authors focus on theentropy optimization problems in finite di

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0884-8289 y .entropy. .optimization techniques. with completecomfort and ease. With this consideration, the authors focus on theentropy optimization problems in finite di978-1-4613-7810-5978-1-4615-6131-6Series ISSN 0884-8289 Series E-ISSN 2214-7934

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Other Important Upwelling Systems,ion of 0 ln 0 = 0, we define the quantity . to be the cross-entropy of x with respect to ., in a general sense. Note that when x and p are both probability distributions, i.e., . this quantity becomes the commonly defined cross-entropy between the two probability distributions (see Chapter 1).

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Uranium - Past and Future Challengesrposes. In a penalty approach, any point outside of the feasible region is assigned a penalty while, in a barrier approach, those feasible solutions near the boundary of the feasible region are subject to a penalty. Both approaches are designed to prevent the search process for an optimal solution f

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https://doi.org/10.1007/978-3-540-78554-5ntly in developing interior-point methods [3, 17, 4, 13, 18]. However, the idea of perturbing the feasible region has not been fully explored. This chapter focuses on this idea and discusses a particular approach involving the ..-norm of a vector measure of constraint violation. Three topics will be