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Download Ziena Optimization KNITRO v6.0 crack by EAT

Added to site2009-07-26
Rating91/100
Votes21


Ziena_Optimization_KNITRO_v6_crack.zip (153948 bytes)

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EAT.nfo 29205 4899
FILE_ID.DIZ 46 46
Ziena_Optimization_KNITRO_v6_crack.exe 166400 148539

EAT.nfo

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                     ■       E A T  P R E S E N T S      ■

                  Ziena.Optimization.KNITRO.v6.0.Cracked-EAT                  



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░██    ▒  SUPPLIER ....: TEAM EAT                                       ▒    ██░
▐█▌    ▒  PROG TYPE ...: SCIENTIFIC                                     ▒    ▐█▌
██     ░  LANGUAGE ....: ENGLISH                                        ░     ██
█▌        RELEASE DATE.: 07/26/09                                             ▐█
█      ░                                                                ░      █
█     ░   CRACKER ......: TEAM EAT                                       ░     █
█         PROTECTION ...: DEMO-LIMITS                                          █
█         DIFFICULTY ...: GUESS!                                               █
█                                                                              █
█         PACKAGER ....: TEAM EAT                                              █
█         FORMAT ......: ZIP/RAR                                               █
█         ARCHIVE NAME.: eatzkn60.zip                                          █
█         No OF DISKS .: [XX/01]                                               █
█                                                                              █
█         REQUIREMENTS .: WinXP/2003/Vista/2008                                █
█         PRICE ........: $5000.00                                             █
█         WEBSITE.......: http://www.ziena.com                                 █
█                                                                              █
█▌                                                                            ▐█
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█             NOTE: This release require AMPL or Matlab interface.             █
█                                                                              █
█                                  **********                                  █
█                                                                              █
█             KNITRO is a solver for nonlinear optimization. It is             █
█             the most powerful and versatile solver on the                    █
█             market, providing three state-of-the-art algorithms.             █
█             The broad range of behaviors exhibited by nonlinear              █
█             problems makes this an essential feature.                        █
█                                                                              █
█             KNITRO is designed for large problems with                       █
█             dimensions running into the hundred thousands. It is             █
█             effective for solving linear, quadratic, and                     █
█             nonlinear smooth optimization problems, both convex              █
█             and nonconvex. It is also effective for nonlinear                █
█             regression, problems with complementarity                        █
█             constraints (MPCCs or MPECs), and mixed-integer                  █
█             programming (MIPs), particular convex mixed integer,             █
█             nonlinear problems (MINLP). KNITRO is highly                     █
█             regarded for its robustness and efficiency.                      █
█                                                                              █
█             KNITRO provides a wide range of user options, and                █
█             offers interfaces to C, C++, Fortran, Java, AMPL,                █
█             AIMMS, GAMS, MPL, Mathematica, MATLAB Microsoft                  █
█             Excel, and LabVIEW. Continuing active development                █
█             and support ensures that KNITRO will remain the                  █
█             leader in nonlinear optimization.                                █
█                                                                              █
█             KNITRO provides 3 state-of-the-art                               █
█             algorithms/solvers for solving problems. Each                    █
█             algorithm addresses the full range of nonlinear                  █
█             optimization problems, and each is constructed for               █
█             maximal large-scale efficiency.                                  █
█                                                                              █
█             * Interior-point Direct algorithm applies barrier                █
█               techniques and directly factorizes the KKT matrix              █
█               of the nonlinear system. It performs best on                   █
█               ill-conditioned problems.                                      █
█                                                                              █
█             * Interior-point CG algorithm applies barrier                    █
█               techniques using the conjugate gradient method to              █
█               solve KKT subproblems. It provides an alternative              █
█               to the Interior-point Direct algorithm when the                █
█               KKT factorization is impractical or inefficent to              █
█               form.                                                          █
█                                                                              █
█             * Active Set algorithm combines classical active set             █
█               principles with a novel linear programming                     █
█               subproblem to rapidly discover the set of binding              █
█               constraints. It's behavior is significantly                    █
█               different from Interior-point algorithms, and it               █
█               converges precisely to the active set to provide               █
█               highly accurate sensitivity information.                       █
█                                                                              █
█             Every nonlinear optimization problem is unique, and              █
█             it can be quite difficult to predict performance of              █
█             any algorithm on a given problem. Choosing among                 █
█             KNITRO's three algorithms greatly increases the                  █
█             chances of solving your problem efficiently.                     █
█                                                                              █
█             KNITRO 6.0 introduces new features for solving                   █
█             optimization models (both linear and nonlinear) with             █
█             binary or integer variables. The KNITRO mixed                    █
█             integer programming (MIP) code offers two algorithms             █
█             for mixed-integer nonlinear programming (MINLP). The             █
█             first is a nonlinear branch and bound method and the             █
█             second implements the hybrid Quesada-Grossman method             █
█             for convex MINLP. The KNITRO MINLP code is designed              █
█             for convex mixed integer programming and is a                    █
█             heuristic for nonconvex problems. The MIP code also              █
█             handles mixed integer linear programs (MILP) of                  █
█             moderate size. Many new user options beginning with              █
█             "mip_*" have been added to offer user control over               █
█             the MIP methods. In addition, the KNITRO multi-start             █
█             generation of new start points is improved and the               █
█             new user option "ms_maxbndrange" was added. See more             █
█             details in the KNITRO 6.0 User's Manual and in the               █
█             MINLP examples provided with the distribution.                   █
█▌                                                                            ▐█
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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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█             1. Unpack to a folder of your choice.                            █
█             2. RTFM to interface it correctly with AMPL/Matlab.              █
█             3. Start using it as it's already fixed.                         █
█                                                                              █
█             That's all. Have fun using it! ;-)                               █
█▌                                                                            ▐█
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▄██▄ ██▌                     ▐▓   EAT  CONTACT   ▓▌                     ▐██ ▄██▄
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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 

FILE_ID.DIZ

EAT's crack for Ziena Optimization KNITRO v6.0


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