HOPSPACK solves derivative-free optimization problems in a C++ software framework. The framework enables parallel operation using MPI (for distributed machine architectures) and multithreading (for single machines with multiple processors or cores). Optimization problems can be very general: functions can be noisy, nonsmooth, and nonconvex, linear and nonlinear constraints are supported, and variables may be continuous or integer-valued.
JCGO (pronounced as "j-c-go") translates (converts) programs written in Java into platform-independent C code that can be compiled (by third-party tools) into highly-optimized native code for the target platform. JCGO is a powerful solution that enables your desktop, server-side, embedded, mobile, and wireless Java applications to take full advantage of the underlying hardware. In addition, JCGO makes your programs, when compiled to native code, as hard to reverse engineer as if they were written in C/C++. The JCGO translator uses some optimization algorithms that allow, together with optimizations performed by a C compiler, the resulting executable code to reach better performance compared with the traditional Java implementations (based on the Just-In-Time technology). The produced executable does not contain nor require a Java Virtual Machine to execute, so its resource requirements are smaller than that required by a typical Java VM. This also simplifies the process of deployment and distribution of an application.
Japplis Website Optimizer Lite is a program to optimize your Web pages. Using several techniques, it can reduce the size of your HTML pages by more than half. This will not only make your Web site faster, but also save bandwidth. Japplis Website Optimizer Lite can also add the height, width, and alt attributes to images if they are missing.
NLopt is a library for nonlinear optimization that allows one to select from a wide variety of optimization algorithms by changing a single parameter. Its features include both local and global optimization, unconstrained, bound-constrained, or nonlinear-inequality constrained problems, and optimization using function values only or using derivatives if they are available. It was initially begun as a wrapper around several existing optimization packages, but it now also includes original implementations of several algorithms for which no free code was available. It provides interfaces callable from C/C++, Fortran, Matlab, GNU Octave, Python, and GNU Guile.
Orc is a library and set of tools for compiling and executing very simple programs that operate on arrays of data. The "language" is a generic assembly language that represents many of the features available in SIMD architectures, including saturated addition and subtraction, and many arithmetic operations.
Simulated annealing is a computational algorithm for optimization. It mimics the physical process of thermal annealing in which a metal is heated and then slowly cooled to settle into a highly ordered crystal structure. For common metals, the lowest energy state is already known. But the method is useful for other problems where the best state is not known and exhaustively searching all possible states is impractical. The method is applied by modeling the problem as a physical system with structure, energy, and temperature. This Python module implements simulated annealing so that it can be easily applied to a variety of problems. An example program is include to perform simulated annealing of the traveling salesman problem.
ca-ga is a toy artificial life simulation that uses genetic algorithms on large cellular automata. It uses simple but easily extended DNA that is 8k long by default, though you can take the size out to anything you have time to evolve. It sits under each cell of a 128x128 board and orders operations to transfer energy in the hopes of achieving a kill and breed. The simulation features a mutating fitness function, emergent sex, and a proof of concept real world fitness function. After enough generations, the cells or genes could achieve collectivism and organismhood, coordinating the values of the hotspots that determine board temperature in order to maintain a desired equilibrium. But maybe not. If you work in a fitness function, an optimizing problem solver results.