Some Multi Convex Programming Problems Arising in Multivariate Sampling
نویسندگان
چکیده
The problems of multivariate sampling arising in the areas of stratified random sampling, two stage sampling, double sampling and response errors formulate as multiobjective convex programming problems with convex objective functions and a single linear constraint with some upper and lower bounds.
منابع مشابه
Optimality and Duality for an Efficient Solution of Multiobjective Nonlinear Fractional Programming Problem Involving Semilocally Convex Functions
In this paper, the problem under consideration is multiobjective non-linear fractional programming problem involving semilocally convex and related functions. We have discussed the interrelation between the solution sets involving properly efficient solutions of multiobjective fractional programming and corresponding scalar fractional programming problem. Necessary and sufficient optimality...
متن کاملA bi-level linear programming problem for computing the nadir point in MOLP
Computing the exact ideal and nadir criterion values is a very important subject in multi-objective linear programming (MOLP) problems. In fact, these values define the ideal and nadir points as lower and upper bounds on the nondominated points. Whereas determining the ideal point is an easy work, because it is equivalent to optimize a convex function (linear function) over a con...
متن کاملShort-term Price-based Unit Commitment of Hydrothermal GenCos: A Pre-emptive Goal Programming Approach
The solution of single-objective unit commitment problems for generation companies participating in deregulated markets may not directly be implementable mainly because of neglecting some conflicting secondary objectives arising from policy-making at internal/external environment. Benefiting an efficient multi-objective approach to improve the applicability of price-based unit commitment soluti...
متن کاملConvex Generalized Semi-Infinite Programming Problems with Constraint Sets: Necessary Conditions
We consider generalized semi-infinite programming problems in which the index set of the inequality constraints depends on the decision vector and all emerging functions are assumed to be convex. Considering a lower level constraint qualification, we derive a formula for estimating the subdifferential of the value function. Finally, we establish the Fritz-John necessary optimality con...
متن کاملA Recurrent Neural Network for Solving Strictly Convex Quadratic Programming Problems
In this paper we present an improved neural network to solve strictly convex quadratic programming(QP) problem. The proposed model is derived based on a piecewise equation correspond to optimality condition of convex (QP) problem and has a lower structure complexity respect to the other existing neural network model for solving such problems. In theoretical aspect, stability and global converge...
متن کامل