Learn the main differences between linear and nonlinear programming, examples of problems that require each method, and tips to identify the best method. Skip to main content LinkedIn.

Finally some numerical examples are given to show the efficiency of the proposed approach to solve approximately constraints nonlinear non-smooth programming problems. Mathematical subject ...

K. Deb, Nonlinear Goal Programming Using Multi-Objective Genetic Algorithms, The Journal of the Operational Research Society, Vol. 52, No. 3 (Mar., 2001), pp. 291-302 Free online reading for over 10 ...

Abstract: The purpose of this paper is to develop a nonlinear programming method for solving a type of cooperative games in which there are multiple objectives and coalitions' values on objectives are ...

Extensive computational examples with up to 150 distribution centers and 150 retailers are presented to illustrate the performance of the algorithms and to compare them with the full-space solution. .

Xin-wei Liu, Ya-xiang Yuan, A ROBUST TRUST REGION ALGORITHM FOR SOLVING GENERAL NONLINEAR PROGRAMMING, Journal of Computational Mathematics, Vol. 19, No. 3 (May 2001), pp. 309-322 Free online reading ...

A burst waveform is a finite sequence of pulses with a staggered PRF. It is used as a high-resolution radar waveform. The ambiguity function of a burst waveform has a good peak-to-sidelobe ratio along ...

Mixed-Integer Nonlinear Programming (MINLP): An optimisation framework that integrates discrete variables with continuous nonlinear functions to model complex decision-making problems.