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▒■▀ SINCE 2000 ▀■▒
▀ ▀
■ E A T P R E S E N T S ■
Gurobi.Optimization.Gurobi.for.AMPL.v4.5.1.Cracked-EAT
■ ■
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░██ ▒ SUPPLIER ....: TEAM EAT ▒ ██░
▐█▌ ▒ PROG TYPE ...: SCIENTIFIC ▒ ▐█▌
██ ░ LANGUAGE ....: ENGLISH ░ ██
█▌ RELEASE DATE.: 2011-06-15 ▐█
█ ░ ░ █
█ ░ CRACKER ......: TEAM EAT ░ █
█ PROTECTION ...: DEMO-LIMITS █
█ DIFFICULTY ...: GUESS! █
█ █
█ PACKAGER ....: TEAM EAT █
█ FORMAT ......: ZIP/RAR █
█ ARCHIVE NAME.: eatga451.zip █
█ No OF DISKS .: [XX/01] █
█ █
█ REQUIREMENTS .: WinXP/Vista/Win7 █
█ PRICE ........: $8,500.00 █
█ WEBSITE.......: http://www.gurobi.com █
█ http://www.ampl.com █
█ █
█▌ ▐█
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█ NOTE: This release requires AMPL, so just RTFM. :) █
█ █
█ ********** █
█ The Gurobi Optimizer is a state-of-the-art solver █
█ for linear programming (LP), quadratic programming █
█ (QP) and mixed-integer programming (MILP and MIQP). █
█ It was designed from the ground up to exploit modern █
█ multi-core processors. Every Gurobi license allows █
█ parallel processing, and the Gurobi Parallel █
█ Optimizer is deterministic: two separate runs on the █
█ same model will produce identical solution paths. █
█ █
█ For solving LP and QP models, the Gurobi Optimizer █
█ includes high-performance implementations of the █
█ primal simplex method, the dual simplex method, and █
█ a parallel barrier solver. For MILP and MIQP models, █
█ the Gurobi Optimizer incorporates the latest methods █
█ including cutting planes and powerful solution █
█ heuristics. All models benefit from advanced █
█ presolve methods to simplify models and slash solve █
█ times. █
█ █
█ The Gurobi Optimizer is written in C and is █
█ accessible from several languages. In addition to a █
█ powerful, interactive Python interface and a █
█ matrix-oriented C interface, we provide █
█ object-oriented interfaces from C++, Java, Python, █
█ and the .NET languages. These interfaces have all █
█ been designed to be lightweight and easy to use, █
█ with the goal of greatly enhancing the accessibility █
█ of our products. And since the interfaces are █
█ lightweight, they are faster and use less memory █
█ than other standard interfaces. Our online █
█ documentation (Quick Start Guide, Example Tour and █
█ Reference Manual) describes the use of these █
█ interfaces. █
█ █
█ Gurobi is also available through several powerful █
█ third-party modeling systems including AIMMS, AMPL, █
█ FRONTLINE SOLVERS, GAMS, MPL, OptimJ and TOMLAB. █
█ █
█ Most of the changes in the 4.5 release of the Gurobi █
█ Optimizer are related to performance. Users of █
█ previous versions will typically not need to make █
█ any changes to their programs to use the new █
█ version. The new version does contain a few new █
█ features, described here. █
█ █
█ * New default Method for continuous models: The █
█ new version uses a new Automatic setting as the █
█ default for solving continuous models. In previous █
█ releases, continuous models were solved with the █
█ dual simplex method by default. While the exact █
█ strategy used by the new Automatic setting may █
█ change in future releases, in this release the new █
█ approach uses the concurrent optimizer for █
█ continuous models with a linear objective (LPs), █
█ the barrier optimizer for continuous models with a █
█ quadratic objective (QPs), and the dual simplex █
█ optimizer for the root node of a MIP model. You █
█ should change the Method parameter if you would █
█ like to choose a different method. █
█ █
█ * New Minimum Releaxation heuristic: The new █
█ version contains a new Minimum Relaxation █
█ heuristic that can be useful for finding solutions █
█ to MIP models where other strategies fail to find █
█ feasible solutions in a reasonable amount of time. █
█ Use the new MinRelNodes parameter to control this █
█ new heuristic. █
█ █
█ * New branch direction control: The new version █
█ allows more control over how the branch-and-cut █
█ tree is explored. Specifically, when a node in the █
█ MIP search is completed and two child nodes, █
█ corresponding to the down branch and the up branch █
█ are created, the new BranchDir parameter allows █
█ you to determine whether the MIP solver will █
█ explore the down branch first, the up branch █
█ first, or whether it will choose the next node █
█ based on a heuristic determination of which █
█ sub-tree appears more promising. █
█ █
█ * Cut pass limit: The new version allows you to █
█ limit the number of cut passes performed during █
█ root cut generation in MIP. Use the new CutPasses █
█ parameter. █
█ █
█ * Additional information for infeasible and █
█ unbounded linear models: The new version allows █
█ you to obtain a Farkas infeasibility proof for █
█ infeasible models, and an unbounded ray for █
█ unbounded models. Use the new InfUnbdInfo █
█ parameter, and the new FarkasProof, FarkasDual, █
█ UnbdRay attributes to obtain this information. █
█▌ ▐█
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░ ▀▓█▄░ COMMENTS ░▄█▓▀ ▀░
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▄ ▄
▄ Do NOT distribute this release outside of the scene ▄
▄ Keep the scene alive and secure! ▄
▄ ▄
All good progs start as freeware,
then things get worse ... ;-)
▀ ▀
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▓█▓█▄▀█▀░▀▓▀█▄ ██▌ INSTALLATION NOTES ▐██ ▄█▀▓▀░▀█▀▄█▓█▓
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▒▐▓█ ▓ ■ `TLB' ■ ▓ █▓▌▒
▒▐██ ▒ Try it, Like it, Buy it! ▒ ██▌▒
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█ 1. Unpack to your AMPL folder. █
█ 2. Start using it as it's already fixed. █
█ █
█ That's all. Have fun using it! ;-) █
█ █
█ ___________________________________________________________________ █
█ █
█ Always remember to block applications (or go off line) from calling █
█ home 'during install'. Once installed, disable 'check for automatic █
█ updates' option if available, so that you don't get it blacklisted. █
█▌ ▐█
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▒ ███ ░ EAT is a closed group. We would consider only: ░ ███ ▒
▒ ███ ░ ░ ███ ▒
░ ██▌ ░ ■ Excellent reverse-engineers ░ ▐██ ░
░▐██ ░ ■ Experienced coders/scripters ░ ██▌░
░██▌ ░ ■ Supplier of quality software who can do so on a ░ ▐██░
▐██ ░ frequent basis (retail date not older then 6 months) ░ ██▌
██▌ ▐██
██▌ We do *NOT* want... ▐██
██ ■ Distros, Shells, etc ██
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█ All our friends out there ... █
█ █
█ Respect goes out to the competition █
█ and to those who keep the scene secure! █
█ █
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