Interval-valued univex functions are introduced for differentiable programming problems. Optimality and duality results are derived for a class of generalized convex optimization problems with interval-valued univex f...
详细信息
Interval-valued univex functions are introduced for differentiable programming problems. Optimality and duality results are derived for a class of generalized convex optimization problems with interval-valued univex functions.
Firstly, definition and methods of reliability assignment are introduced in this paper. And the nonlinear programming based on Lagrange multipliers method is described briefly. Meanwhile the calculation principle and ...
详细信息
ISBN:
(纸本)9781479900305
Firstly, definition and methods of reliability assignment are introduced in this paper. And the nonlinear programming based on Lagrange multipliers method is described briefly. Meanwhile the calculation principle and mathematic model are proposed. Secondly, determining the reliability index is discussed in the paper, and the reliability block diagram and allocation model are given. Base on the discussion before and the fight control with longitudinal pitch motion, the feasibility of the nonlinear programming method is needed to verify. Lastly, the allocated system reliability is bigger than the predicted threshold reliability parameter, which verifies that the used allocation method is feasible and reasonable.
A framework for solving a class of nonlinear programming problems via the filter method is presented. The proposed technique first solve a sequence of quadratic programming subproblems via line search strategy and to ...
详细信息
A framework for solving a class of nonlinear programming problems via the filter method is presented. The proposed technique first solve a sequence of quadratic programming subproblems via line search strategy and to induce global convergence, trial points are accepted provided there is a sufficient decrease in the objective function or constraints violation function. In the event when the step size has reached a minimum threshold such that the trial iterate is rejected by the filter, the algorithm temporarily exits to a trust region based algorithm to generate iterates that approach the feasible region and also acceptable to the filter. Computational results on selected large scale CUTE problems on the prototype code fiILS are very encouraging and numerical performance with LOQO and SNOPT show that the algorithm is efficient and reliable.
In today's business environment, many fresh food companies have complex supply networks to distribute their products. For example, agricultural products are distributed through a multiechelon supply chain which in...
详细信息
In today's business environment, many fresh food companies have complex supply networks to distribute their products. For example, agricultural products are distributed through a multiechelon supply chain which includes agricultural association, agricultural produce marketing corporations (APMCs), markets, and so forth. In this paper a fresh produce supply network model is designed to determine the optimal service area for APMCs, the replenishment cycle time of APMCs, and the freshness-keeping effort, while maximizing the total profit. The objective is to address the integrated facility location, inventory allocation, and freshness-keeping effort problems. This paper develops an algorithm to solve the nonlinear problem, provides numerical analysis to illustrate the proposed solution procedure, and discusses the effects of various system parameters on the decisions and total profits. A real case of an agricultural product supply chain in Taiwan is used to verify the model. Results of this study can serve as a reference for business managers and administrators.
A class of semistrictly G-preinvex functions and optimality in nonlinear programming are further discussed. Firstly, the relationships between semistrictly G-preinvex functions and G-preinvex functions are further dis...
详细信息
A class of semistrictly G-preinvex functions and optimality in nonlinear programming are further discussed. Firstly, the relationships between semistrictly G-preinvex functions and G-preinvex functions are further discussed. Then, two interesting properties of semistrictly G-preinvexity are given. Finally, two optimality results for nonlinear programming problems are obtained under the assumption of semistrict G-preinvexity. The obtained results are new and different from the corresponding ones in the literature. Some examples are given to illustrate our results.
Mechanical positioning of wood blocks in a peeling machine can be considerably improved by means of electronics with respect to the peeled veneer recovery. An opto-electronic measurement system renders log shape descr...
详细信息
Mechanical positioning of wood blocks in a peeling machine can be considerably improved by means of electronics with respect to the peeled veneer recovery. An opto-electronic measurement system renders log shape describing data to be processed in a microcomputer. The form of data is described 10 the paper. A cost function determining the optimal position of the peeling axis and suitable for the real-time optimization is formulated. Searching of the optimal position is described as a nonlinear optimal problem. Further, a solution of the problem using nonlinear programming approach and realizable 10 the real-time conditions is presented in the paper. The economical effects of the optimization are analyzed.
To solve the problem of long logistics delivery time in supply chain, a Mixed Integer Non-linear Program (MINLP) model is built by using Mixed Integer nonlinear programming theory. Firstly, the General algebraic model...
详细信息
To solve the problem of long logistics delivery time in supply chain, a Mixed Integer Non-linear Program (MINLP) model is built by using Mixed Integer nonlinear programming theory. Firstly, the General algebraic modeling system (GAMS) is used to build the model to fully integrate each parameter of logistics transportation, the total distribution time of the supply chain network, the coverage radius of the logistics base, the number of users, the total capacity of the logistics base, the mode of railway and road transportation, the nonlinear programming model is built and solved by DICOPT solver in GAMS. The cost of logistics can be decreased, transportation time can be reduced, and the logistics system's operating efficiency can be increased in the long term with the help of this algorithm. The proper operation of the logistics system is critical in encouraging the supply chain circulation of various industries and has a direct impact on the society's economic development. The optimal logistics distribution plan with 5 logistics bases covered users of 18 and railway capacity of 2. With the same railway capacity and the same total budget, the larger the number of covered users, the greater the total distribution time increases, but the larger the total budget, the growth of the total distribution time slows down significantly. Experiments show that MINLP model can solve the problem of logistics-based layout optimization in nonlinear logistics management.
We introduce some approximate optimal solutions and a generalized augmented Lagrangian in nonlinear programming, establish dual function and dual problem based on the generalized augmented Lagrangian, obtain approxima...
详细信息
We introduce some approximate optimal solutions and a generalized augmented Lagrangian in nonlinear programming, establish dual function and dual problem based on the generalized augmented Lagrangian, obtain approximate KKT necessary optimality condition of the generalized augmented Lagrangian dual problem, prove that the approximate stationary points of generalized augmented Lagrangian problem converge to that of the original problem. Our results improve and generalize some known results. Copyright (C) 2007.
A method for improving local optimal solutions of nonlinear programming problems by treating constraints directly, which is named "Modal Trimming Method", is proposed. This method combines a gradient method ...
详细信息
A method for improving local optimal solutions of nonlinear programming problems by treating constraints directly, which is named "Modal Trimming Method", is proposed. This method combines a gradient method for searching local optimal solutions, with an extended Newton-Raphson method based on the Moore-Penrose generalized inverse of a Jacobian matrix of objective and constraint functions for searching initial feasible solutions used by the gradient method. A strategy for preventing traps into fathomed local optimal solutions is proposed. Some features of the method are investigated qualitatively, and it is found that they are suitable to improve local optimal solutions efficiently. The method is applied to a wide range of problems, and its performance is evaluated in terms of the global optimality of the suboptimal solutions. It turns out that the method has a high possibility of deriving the global optimal solutions by the suboptimal ones for a wide range of problems.
This paper analyses the solution of a specific quadratic sub-problem, along with its possible applications, within both constrained and unconstrained nonlinear programming frameworks. We give evidence that this sub-pr...
详细信息
This paper analyses the solution of a specific quadratic sub-problem, along with its possible applications, within both constrained and unconstrained nonlinear programming frameworks. We give evidence that this sub-problem may appear in a number of Linesearch Based Methods (LBM) schemes, and to some extent it reveals a close analogy with the solution of trust-region sub-problems. Namely, we refer to a two-dimensional structured quadratic problem, where five linear inequality constraints are included. Finally, we detail how to compute an exact global solution of our two-dimensional quadratic sub-problem, exploiting first order Karush-Khun-Tucker (KKT) conditions.
暂无评论