The Algorithm Design Manual
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Programming Challenges

The Stony Brook Algorithm Repository

Steven Skiena
Stony Brook University
Dept. of Computer Science

cGOP - A Package for Global Optimization

cGOP is a package for rigorously solving nonconvex optimization problems to global optimality. The package implements the GOP algorithm using a set of C subroutines to solve these problems using decomposition and branch-and-bound techniques. It also incorporates several improvements made to the original GOP algorithm to reduce the computational complexity, as well as new formulations that permit implicit solutions of some of the subproblems encountered during the algorithmic steps.

The algorithms use local optimization solvers (currently MINOS and CPLEX) to solve linear, mixed-integer linear and convex subproblems. Currently, the package can be used to solve problems with linear constraints. The original algorithm and its derivatives can be accessed by calls to high-level subroutines as well as through a standalone mode for quadratic problems. Furthermore, it can also be accessed using a high-level interface that permits easy description of the problems.

cGOP is designed as a library of subroutines that can be called from any high level programming language. It has been written in portable ANSI C, and is currently available for the HP 9000, IBM RS6000, SUN4 and Silicon Graphics architectures. There are no restrictions on the sizes of problems that can be solved; the algorithms are only limited by the available memory and CPU resources on the machine on which the software is run.

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  • CASL's Computational Tools Page

    Problem Links

    Constrained and Unconstrained Optimization (5)
    Linear Programming (4)

    This page last modified on 2008-07-10 .