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Gurobi Optimization Gurobi v4.5.1

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商品名稱: Gurobi Optimization Gurobi v4.5.1


商品分類: 掃描、PDF、辦公文書工具


商品類型: 智慧引擎提供了新一代的高精確性的描繪軟體


語系版本: 英文正式版


運行平台: Windows XP/Vista/7


更新日期: 2011-07-15




破解說明:



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內容說明:



Gurobi智慧引擎提供了新一代的高精確性的描繪方案。

英文說明:



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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作者: goqrnahe
  (2011-11-10 21:10)
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