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[docs] Simplify the introduction page
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For the documentation of JuMP 0.18, see
[here](https://jump.dev/JuMP.jl/0.18/).

## What is JuMP?

[JuMP](https://github.com/jump-dev/JuMP.jl) is a domain-specific modeling
language for [mathematical
optimization](https://en.wikipedia.org/wiki/Mathematical_optimization) embedded
in [Julia](https://julialang.org/). It currently supports a number of open-source
and commercial solvers (see below) for a variety of problem classes, including
**linear programming**, **mixed-integer programming**, **second-order conic
programming**, **semidefinite programming**, and **nonlinear programming**.
language for [mathematical optimization](https://en.wikipedia.org/wiki/Mathematical_optimization)
embedded in [Julia](https://julialang.org/). It currently supports a number of
open-source and commercial solvers for a variety of problem classes, including
linear, mixed-integer, second-order conic, semidefinite, and nonlinear
programming.

## Resources for getting started

* Checkout the [Installation Guide](@ref).
* Read the [Quick Start Guide](@ref).
* Browse some of our examples, including classics such as [The diet problem](@ref),
or the [Maximum likelihood estimation](@ref) problem using nonlinear
programming.
* Work through more in-depth tutorials at [JuMPTutorials.jl](https://github.com/jump-dev/JuMPTutorials.jl)
* Join the [community forum](https://discourse.julialang.org/c/domain/opt/13) to
search for questions to commonly asked questions.
- Before asking a question, make sure to read [PSA: make it easier to help you](https://discourse.julialang.org/t/psa-make-it-easier-to-help-you/14757),
which contains a number of tips on how to ask a good question.

## Key features

JuMP's features include:

- User friendliness
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- JuMP uses a generic solver-independent interface provided by the
[MathOptInterface](https://github.com/jump-dev/MathOptInterface.jl)
package, making it easy to change between a number of open-source and
commercial optimization software packages ("solvers").
- Currently supported solvers include
[Artelys Knitro](https://artelys.com/en/optimization-tools/knitro),
[Bonmin](https://projects.coin-or.org/Bonmin),
[Cbc](https://projects.coin-or.org/Cbc),
[Clp](https://projects.coin-or.org/Clp),
[Couenne](https://projects.coin-or.org/Couenne),
[CPLEX](https://www.ibm.com/analytics/cplex-optimizer),
[ECOS](https://github.com/ifa-ethz/ecos),
[FICO Xpress](https://www.fico.com/en/products/fico-xpress-optimization-suite),
[GLPK](http://www.gnu.org/software/glpk/),
[Gurobi](https://www.gurobi.com),
[Ipopt](https://projects.coin-or.org/Ipopt),
[MOSEK](https://www.mosek.com/),
[NLopt](https://nlopt.readthedocs.io/en/latest/), and
[SCS](https://github.com/cvxgrp/scs).
commercial optimization software packages ("solvers"). The [Getting Solvers](@ref)
section contains a table of the currently supported solvers.
- Access to advanced algorithmic techniques
- Including efficient LP re-solves which previously required using
solver-specific and/or low-level C++ libraries.
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it can be embedded in commercial software that complies with the terms
of the license.

Although JuMP has not reached version 1.0 yet, the releases are
stable enough for everyday use and are being used in a number of research
projects and neat applications by a growing community of users who are early
adopters. JuMP remains under active development, and we welcome your feedback,
suggestions, and bug reports.

Contents
--------

```@contents
Pages = [
"installation.md",
"quickstart.md",
"variables.md",
"expressions.md",
"objective.md",
"constraints.md",
"containers.md",
"solvers.md",
"solutions.md",
"nlp.md",
"style.md",
"extensions.md",
"roadmap.md"
]
Depth = 2
```

### Citing JuMP

If you find JuMP useful in your work, we kindly request that you cite the
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