### Problems and Software

If you are in search of software for your problem you will find
as far as possible public domain or free-for-research software.
In some cases source code may not be available, some authors only supply
executables for special systems.
In any case, observe the expressed or implied LICENSE conditions !
In most cases these accompany the code. Programs
are in f77 unless indicated otherwise (f90, C/C++, Pascal, Matlab, Java).
Links usually download files directly
or put you in directory if software is not a single file.

If you really need the best possible solution to your problem and have
no information about it, e.g. a currently working solution which needs
improvement only, then you are faced with a problem in

Global optimization is one of centerpoints of current research. Most available
codes for

#### LP/NLP - Linear and Nonlinear Optimization

identify local optimal solutions only. (Of course for linear , convex quadratic
and convex semidefinite problems a local solution is also a global one).
The necessary optimality conditions can also be regarded as a special problem
of zerofinding. The codes in the following area however adress much more
general problems and hence are also weaker in their solution power.
(In most cases, you ** must supply a good initial guess) **.

The necessary optimality conditions for a constrained problem can
also be formulated as a so called

Again this class of problems is much more general. This is also an area of
much active research.
Often a user has not only one objective to optimize but
must compromise between different ones. Then, methods of

must be applied.
Discrete optimization problems require special treatment, as a rule in
a problem specific way. Because of their combinatorial nature computing
effort might be extreme if one aims at exact solutions. But often good
suboptimal solutions can be found by approximation methods.

Often one wants to replace some complicated function expression
by one which is cheap to evaluate or one wants to describe a huge set of
discrete data by a simple analytical expression. Then one is faced with a problem
of

Any approximation problem is an optimization problem, but there exist
specialized and more efficient algorithms.