To address this need, a relatively large but easy-to-use collection of test functions was produced and guidelines for testing the reliability and robustness of unconstrained optimization software were designed. 9 tables. (ERA citation 04:002120)More, J. J...
funconstrainis a pure R implementation of the 35 test functions in the paper byMoré, Garbow, and Hillstromuseful (to varying degrees) for testing unconstrained numerical optimization methods, e.g. those implementing the likes of steepest descent, Newton, BFGS, L-BFGS, conjugate gradient and so...
The SIF optimization test-problem decoder, which used to be a constitutent part of the CUTE environment, has been isolated into a separate package named SifDec. Any software which could require the decoding of a SIF file may now rely on it, as a package in its own right. It is charac...
As for the initial state(s) of the model, the initial value of an unconstrained variable can be any of those allowed by its domain. Thus, the set of initial states is given by states whose variable valuations satisfy all the init constraints in a module. SMV features general arithmetic, ...
If unconstrained by obstacles, an efficient way to reposition and reorient a car is to turn in an arc, using maximum steering angle, towards the new position while making room for the turning arc necessary to also establish correct orientation at the target position. Figure 9 illustrates this ...
smeach of which satisfies the regular expression R. Parameterizing the regular expression conveniently transforms a complex search in the space of satisfying solutions to a regular expression into a search among a set of integer points that are unconstrained. The size of the search space may be ...
Unconstrained optimizationMultistart methodIn general, classical iterative algorithms for optimization, such as Newton-type methods, perform only local search around a given starting point. Such feature is an impediment to the direct use of these methods to global optimization problems, when good ...
Topographical global optimizationQuasi-Newton methodUnconstrained optimizationMultistart methodIn general, classical iterative algorithms for optimization, such as Newton-type methods, perform only local search around a given starting point. Such feature is an impediment to the direct use of th...
Ni, Testing different conjugate gradient methods for large-scale unconstrained optimization, J. Comput. Math., 21 (2003), 331-320.Yu-hong;Dai(LSEC;ICMSEC;Academy;of;Mathematics;and;System;Sciences;Chinese;Academy;of;Sciences;Beijing;100080;China)QinNi;(College;of;Science;Nanjing;University;of;...
funconstrainis a pure R implementation of the 35 test functions in the paper byMoré, Garbow, and Hillstromuseful (to varying degrees) for testing unconstrained numerical optimization methods, e.g. those implementing the likes of steepest descent, Newton, BFGS, L-BFGS, conjugate gradient and so...