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■ E A T P R E S E N T S ■
Gurobi.Optimization.Gurobi.for.AMPL.v4.0.0.Cracked-EAT
■ ■
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░██ ▒ SUPPLIER ....: TEAM EAT ▒ ██░
▐█▌ ▒ PROG TYPE ...: SCIENTIFIC ▒ ▐█▌
██ ░ LANGUAGE ....: ENGLISH ░ ██
█▌ RELEASE DATE.: 2010-11-22 ▐█
█ ░ ░ █
█ ░ CRACKER ......: TEAM EAT ░ █
█ PROTECTION ...: DEMO-LIMITS █
█ DIFFICULTY ...: GUESS! █
█ █
█ PACKAGER ....: TEAM EAT █
█ FORMAT ......: ZIP/RAR █
█ ARCHIVE NAME.: eatga400.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. █
█ █
█ Version 4.0 of the Gurobi Optimizer includes a █
█ number of enhancements. Users of previous versions █
█ may need to make a few minor changes to their █
█ existing programs. Here are the new features, and █
█ the likely changes required to existing programs. █
█ █
█ New features: █
█ * Quadratic programming: The Gurobi Optimizer now █
█ supports models with quadratic objective █
█ functions. The new version includes primal █
█ simplex, dual simplex, and parallel barrier █
█ optimizers for continuous QP models, and a █
█ parallel branch-and-cut solver for Mixed Integer █
█ Quadratic Programming (MIQP) models. █
█ * Concurrent optimizer: The Gurobi Optimizer now █
█ allows you to run multiple algorithms █
█ simultaneously when solving a linear continuous █
█ model on a multi-core machine. The optimizer █
█ returns when the first algorithm solves the model. █
█ We include both a standard concurrent optimizer █
█ and a deterministic concurrent optimizer. The █
█ latter returns the exact same solution every time █
█ you run it, while the former can sometimes return █
█ different optimal solutions from one run to the █
█ next. The former can sometimes be significantly █
█ faster. █
█ * MIP performance: The MIP solver is faster in █
█ release 4.0. These improvements do not require any █
█ parameter changes. █
█ * LP performance: The simplex and barrier solvers █
█ are slightly faster in release 4.0. We have also █
█ improved the numerical stability of the primal █
█ simplex solver and the barrier crossover █
█ algorithm. █
█ * Delayed MIP strategy change: The Gurobi Optimizer █
█ now gives you the option to change a few MIP █
█ parameters in the middle of the optimization in █
█ order to dynamically shift the search strategy. █
█ Specifically, two new parameters, ImproveStartGap █
█ and ImproveStartTime, allow you to specify when █
█ the algorithm should modify the values of a few █
█ parameters that control the intensity of the MIP █
█ heuristics. By setting one or both of these █
█ parameters to non-default values, you can cause █
█ the MIP solver to switch from its standard █
█ parameter settings, where it tries to strike a █
█ balance between finding better solutions and █
█ proving that the current solution is optimal, to a █
█ set of parameter values that focus almost entirely █
█ on finding better solutions. █
█ * Support for Visual Studio 2010: Gurobi Optimizer █
█ now supports Microsoft Visual Studio 2010. This █
█ change only affects C++ users, who will find new █
█ libraries gurobi_c++2010md.lib, █
█ gurobi_c++2010mdd.lib, gurobi_c++2010mt.lib, and █
█ gurobi_c++2010mtd.lib in the lib directory of the █
█ Gurobi distribution. █
█ * Explicit license release in Java and .NET: The new █
█ version includes an explicit method for releasing █
█ a Gurobi license. You no longer need to rely on █
█ the garbage collector to reclaim unused licenses. █
█ * New methods, attributes, parameters, and error █
█ codes: To support the new features in Gurobi 4.0, █
█ we have added several new methods, attributes, █
█ parameters, and error codes. You can learn more █
█ about these in the {Gurobi Reference Manual}. █
█ █
█ New methods: █
█ * New C methods for managing Q: the C interface █
█ includes three new routines, GRBaddqpterms, █
█ GRBdelq, and GRBgetq. These allow you to add, █
█ delete, and retrieve quadratic objective terms, █
█ respectively. █
█ * Quadratic expressions: the object oriented █
█ interfaces include a new quadratic expression █
█ class, GRBQuadExpr, which can be used to build █
█ quadratic objective functions. █
█ * getObjective/setObjective: the object oriented █
█ interfaces include new GRBModel methods that allow █
█ you to retrieve the current objective function as █
█ a linear or quadratic expression, and allow you to █
█ set the objective equal to a linear or quadratic █
█ expression. █
█ * getValue: the object oriented interfaces include a █
█ new getValue method that allows you to compute the █
█ value of a GRBLinExpr or GRBQuadExpr object for █
█ the current solution. █
█ * License release: the Java and .NET interfaces █
█ include a new release method that allows you to █
█ release the license held by an environment █
█ immediately, instead of having to wait for the █
█ garbage collector to reclaim the GRBEnv object. █
█ █
█ New attributes: █
█ * IsQP: model attribute that indicates whether the █
█ model has any quadratic terms. █
█ * NumQNZs: model attribute that returns the number █
█ of quadratic terms in the objective function. █
█ █
█ New parameters: █
█ * Method: the previous LPMethod parameter has been █
█ renamed to Method. This new parameter controls the █
█ algorithm used to solve continuous linear and █
█ quadratic models. We have added two new options: █
█ concurrent and deterministic concurrent. This █
█ parameter also selects the algorithm used to solve █
█ the root node of a MIP model. █
█ * NodeMethod: chooses the algorithm used to solve █
█ node relaxations in a MIP model. █
█ * ModKCuts: controls the generation of mod-k cuts. █
█ * ImproveStartGap: allows you to specify the █
█ optimality gap at which the MIP solver resets a █
█ few MIP heuristics parameters in order to shift █
█ the attention of the MIP solver to finding the █
█ best possible feasible solution. █
█ * ImproveStartTime: allows you to specify the █
█ elapsed time at which the MIP solver resets a few █
█ MIP heuristics parameters in order to shift the █
█ attention of the MIP solver to finding the best █
█ possible feasible solution. █
█ * PreMIQPMethod: chooses the presolve transformation █
█ performed on MIQP models. █
█ * PSDTol: sets a limit on the amount of diagonal █
█ perturbation that the optimizer is allowed to do █
█ on the Q matrix for a quadratic model. If a larger █
█ perturbation is required, the optimizer will █
█ terminate with an GRB_ERROR_Q_NOT_PSD error. █
█ █
█ New error codes: █
█ * GRB_ERROR_Q_NOT_PSD: This new error code is █
█ returned when you attempt to solve a QP model █
█ where the Q matrix is not positive semi-definite █
█ (meaning there exists an x for which x'Qx ). Note █
█ that the optimizer will always try to add a small █
█ perturbation to the diagonal to correct small PSD █
█ violations. This error will be reported when the █
█ required perturbation is too large (as controlled █
█ by the new PSDTol parameter). █
█▌ ▐█
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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 ██
█▌ ░ ■ Carders █
█ ░ ■ Couriers ░ █
█ █
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█ All our friends out there ... █
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