the objective function

The objective function that minimizes the maximal link utilization is usually adopted to avoid the network congestion.

Taken the velocity and pressure at the bottom as the objective function, the structure parameters of rotary nozzle were optimized.

For the efficiency of the objective function, the efficiency of an optimized runner is better than the original runner.

The total annual cost (TAC) was adopted as the objective function for process optimization.

A stable solution of an ill-posed inverse problem can be obtained by utilizing the regularization methods in the objective function.

The objective function increases in the direction of the directional derivative of the objective function.

This presents difficulties for most conventional optimization methods, which need derivative information of the objective function.

In Stochastic Model Predictive Control, chance constraints are presented and the objective function is an mathematical expectation.

The objective function of the model is piecewise continuous function. The model was solved by the iterative linear program.

Then the linearization of the objective function is introduced to overcome the difficulty of choosing an appropriate penalty coefficient.

The objective function of the model was to minimize the make span and the maximum tardiness.

The objective function and state variables through the method of least squares approximation obtained by the design variables.

Finally, the basic projection pursuit clustering model is improved, in particularly the improvement of the objective function.

The objective function of distribution network reconfiguration is established as minimizing the network loss.

The gradients of the objective function with respect to the parameters are obtained through perturbation method.

Structural parameters of aluminum hull are firstly optimized using minimal mass as the objective function.

Finally, a convenient optimal dispatch scheme is obtained by decomposing each original scene and simplifying the objective function.

Conclusion The objective function is valid and efficient for clinical application in IMRT inverse planning optimization.

In optimization, the restriction condition is heat insulation performance and the objective function is danger coefficient.

The objective function can be realized using a conjugate gradient approach.

The first section says that the solution found is integer optimal, and that the value found for the objective function is 23, a minimum.

Then the objective function is minimized via standard gradient-based optimization algorithm.

To solve this problem, this paper introduces pseudo-likelihood approach instead of likelihood approach to construct the objective function.

Therefore, the x2 variable would change the value of the objective function by 0 if it could ever be relaxed.

The first section shows that the solution is optimal and that the objective function equals approximately 172667.

By optimizing the objective function with the gradient method the iterative formula about the medium velocity is obtained.

The objective function for these critical points are the same, regardless.

This very simple program declares the two decision variables: the constraint and the objective function.

The objective function can be built based on the finite difference modeling for the wave equation.

Based on the calculation of power flow analysis, the objective function is minimized to obtain the near-optimal energy purchase strategy.

increase of BHF as high as possible and avoidance of the fracture limit according to the objective function.

The objective function is the cost of beam .

This paper mainly concerns two critical issues of IMRT: the objective function and the convolution kernels based on Monte Carlo method.

In the end, the objective function is discussed and the optimal control model proved simple and practical.

we calculated the objective function (Y) of weighted least squares method, which is the residual sum of squares.

In other words, a change in x2 won't change the objective function's value, given that the constraint holds for the new (x1, x2) pair.

A bounded constraint prevents the objective function from reaching a better value.

The objective function is to minimize total resource consumption of setup time and jobs under makespan constrains.

The objective function is the minimum power loss.

The solution is optimal and the objective function value is 5.

For example, in the objective function, the coefficients 3 and 1 are part of the problem's data set.

In the case of general recourse matrix, we discuss the convexity of feasible set and the convexity of the objective function;

The convexity of feasible set, and the convexity, the continuity and the differentiability of the objective function are studied;

The Objective Function Study of Single Target Group Policy Decision

The Optimum Design of the Objective Function for the Transmission of Cylindrical Gears

Research on the Objective Function Minimization Standards in the Regression Analysis

Study on the Properties of the Objective Function for Assessing Roundness Errors

Solving Two-stage Stochastic Programming with Recourse in the Objective Function's Empirical Mean

Precise information about the status of the objective function and about the constraints

Information about the problem and the optimal value of the objective function

Study on the Objective Function for the Array Pattern Synthesis Based on Genetic Algorithm

In order to use genetic algorithms to solve facilities layout planning, making the objective function into fitness function;