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Xpress was originally developed by Dash Optimization, and was acquired by FICO in 2008. [3] Its initial authors were Bob Daniel and Robert Ashford. The first version of Xpress could only solve LPs; support for MIPs was added in 1986. Being released in 1983, Xpress was the first commercial LP and MIP solver running on PCs. [4]
Given a system transforming a set of inputs to output values, described by a mathematical function f, optimization refers to the generation and selection of the best solution from some set of available alternatives, [1] by systematically choosing input values from within an allowed set, computing the value of the function, and recording the best value found during the process.
Among these solvers are BARON, COIN-OR solvers, CONOPT, COPT Cardinal Optimizer, CPLEX, DICOPT, IPOPT, MOSEK, SNOPT, and XPRESS. GAMS allows the users to implement a sort of hybrid algorithm combining different solvers. Models are described in concise, human-readable algebraic statements. GAMS is among the most popular input formats for the ...
Provides warnings if tagged parameters do not match code, parsed parameters included in XML output and Doxygen-style tagfile (-D flag in 8.7). Partial C preprocessor support with -p flag. Support for #if/#ifdef control over documentation inclusion using the -D and -U command-line flags. Imagix 4D: customizable through style sheets and CSS
OR-Tools was created by Laurent Perron in 2011. [5]In 2014, Google's open source linear programming solver, GLOP, was released as part of OR-Tools. [1]The CP-SAT solver [6] bundled with OR-Tools has been consistently winning gold medals in the MiniZinc Challenge, [7] an international constraint programming competition.
Software documentation is written text or illustration that accompanies computer software or is embedded in the source code. The documentation either explains how the software operates or how to use it, and may mean different things to people in different roles. Documentation is an important part of software engineering. Types of documentation ...
The IBM ILOG CPLEX Optimizer solves integer programming problems, very large [3] linear programming problems using either primal or dual variants of the simplex method or the barrier interior point method, convex and non-convex quadratic programming problems, and convex quadratically constrained problems (solved via second-order cone programming, or SOCP).
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