Xiaoning Xu, Feng He, Rong Chen, Qingzhi Zhang, Solving non-linear portfolio optimization problems with interval analysis, The Journal of the Operational Research Society, Vol. 66, No. 6 (JUNE 2015), ...

The global optimization solver gives users a better way to tackle complex nonlinear problems in energy, pricing optimization and many other fields, and can offer guarantees about the performance ...

Moreover, nonlinear optimization can be computationally expensive in terms of time and memory, so care must be taken when matching an algorithm to a problem. All optimization techniques in PROC NLP ...

When solving the general smooth nonlinear and possibly nonconvex optimization problem involving equality and/or inequality constraints, an approximate first-order critical point of accuracy ϵ can be ...

On the other hand, the introduction of nonlinear activation functions enables HOLO's optimization method to better address non-convex optimization problems.

The authors' optimization procedures stem from Lagrangian methods for approaching nonlinear problems, and demonstrate an efficient, exact means of calculating the shape derivative of the cost ...

The global optimization solver gives users a better way to tackle complex nonlinear problems in energy, pricing optimization and many other fields, and can offer guarantees about the performance of ...

No algorithm for optimizing general nonlinear functions exists that always finds the global optimum for a general nonlinear minimization problem in a reasonable amount of time. Since no single ...