Solvers: add link to request trials and fix the presentation of paral…

…lel links

docs/source/more/faq.md

@@ -1,7 +1,7 @@
 (faq)=
 # FAQs
 
-## What is AMPL?
+## What is AMPL
 
 1. AMPL is a modelling language for describing production, distribution, blending, scheduling and many other kinds of problems known generally as large-scale optimization or mathematical programming.
 
@@ -11,7 +11,7 @@
 
 4. **You can use AMPL for free** with open-source solvers with a [Community Edition License](https://ampl.com/ce/) for personal, academic, or commercial prototyping purposes using [AMPL APIs](../ampl/apis.rst). You can also start 30-day trials for individual commercial solvers. We also offer a few other free licenses for you to [start for free now](https://ampl.com/start-free-now/).
 
-## How to install AMPL?
+## How to Install AMPL
 
 After downloading your AMPL & Solvers bundle from the [AMPL Portal](https://portal.ampl.com),
 please follow the instructions below that correspond to your operating system:
@@ -20,7 +20,7 @@ please follow the instructions below that correspond to your operating system:
 - [macOS](../ampl/install.md#macos)
 
 (cloud_licenses)=
-## How do cloud licenses work?
+## How do Cloud Licenses Work
 
 Instead of using long term licenses that require static hardware we use short-term leases which give the flexibility of moving the license between different machines or containers.
 
@@ -32,7 +32,7 @@ If everything is ok with the request, a new lease is returned in the response an
 
 Even though this mechanism was designed with Docker containers in mind, it also works natively on Windows and macOS virtual and physical machines too. The only requirement is an internet connection.
 
-### Which information is collected?
+### Which Information is Collected?
 
 The fingerprint information sent in each request includes among other details the following: 
   - number of CPU cores on the underlying machine
@@ -52,7 +52,7 @@ If a license is exceeding its limitations for long periods of time users are the
 
 You can check the status of AMPL cloud services at <https://status.ampl.com/>.
 
-## How to use AMPL with Docker containers?
+## How to Use AMPL with Docker Containers
 
 AMPL can be easily used on [Docker containers](https://www.docker.com/):
 
@@ -70,7 +70,7 @@ In this example, we use the image [`python:3.9-slim-bullseye`](https://hub.docke
 
 In the example above we used a Python container, for other options see [AMPL on Docker Containers](ampl_docker).
 
-## How to add AMPL installation directory to PATH/Path?
+## How to Add AMPL Installation Directory to PATH/Path?
 
 ### Windows
 
@@ -106,7 +106,7 @@ os.environ["PATH"] += os.pathsep + "/complete/path/to/ampl/installation/director
 
 Note: on Windows you should replace `"PATH"` by `"Path"`.
 
-## Other help resources
+## Other Help Resources
 
 ```{toctree}
 ../help/index

docs/source/more/new.md

@@ -41,14 +41,79 @@ Get your free license at: **<https://ampl.com/ce>**
 -   [It works with Docker Containers and Cloud Functions (e.g., AWS Lambda, Azure Functions, etc.)](ampl_docker)
 -   Since it is a [cloud license](cloud_licenses) it can be used on continuous integration and continuous delivery (CI/CD) platforms.
 
-## Using AMPL in Google Colab, Kaggle, and similar platforms
+## Using AMPL in Google Colab, Kaggle, and Similar Platforms
 
 We have a set of Jupyter Notebooks available on our [Model Colaboratory](https://ampl.com/colab/).
 
 You can use our template (<https://ampl.com/colab/tags/template.html>)
 as a starting point. Our cloud licenses, including AMPL CE licenses, work on all cloud platforms.
 
-## Snapshot feature (save and restore AMPL sessions)
+## Enhanced Solver Drivers with Automatic Reformulations
+
+We have released new [MP-Based](https://mp.ampl.com/model-guide.html) solver
+drivers for [Gurobi](../solvers/gurobi/index.md), [CPLEX](../solvers/cplex/index.md), [XPRESS](../solvers/xpress/index.md), [COPT](../solvers/copt/index.md), [MOSEK](../solvers/mosek/index.md),
+[BARON](../solvers/baron/index.md), among others. They are included in the [AMPL distribution bundle](https://portal.ampl.com).
+
+The new solver drivers have the following features:
+
+- Full support of logical expressions and constraints, as described in the AMPL page on Logic and Constraint Programming Extensions.
+- Algebraic expressions beyond linear and quadratic.
+- Choice between conversions in the driver vs. native solver support.
+
+[[Modeling Guide](https://mp.ampl.com/model-guide.html)]
+
+### New AMPL-Solver Interface Library
+
+We're rolling out a new AMPL-solver interface library that significantly
+expands the range of model expressions that can be used with popular
+solvers.
+
+Modeling languages aim to let you describe
+optimization models to a computer in much the same way that you describe
+models to other people. The newly extended ["MP" interface](https://github.com/ampl/mp)
+brings AMPL closer to this goal, by allowing expanded use of a variety of convenient
+expressions in objectives and constraints. Notable examples include:
+
+- Conditional operators: `if-then-else`; `==>`, `<==`, `<==>`
+- Logical operators: `or`, `and`, `not`; `exists`, `forall`
+- Piecewise linear functions: `abs`; `min`, `max`; `<<breakpoints;slopes>>`
+- Counting operators: `count`; `atmost`, `atleast`, `exactly`; `numberof`
+- Comparison operators: `>`, `<`, `!=`; `alldiff`
+
+These operators can be applied to general forms of AMPL expressions, and
+thus can be used together in objective and constraint specifications. The
+new interface also helps solvers to accept nonlinear operators (`*`, `/`, `^`) in
+a broader variety of circumstances.
+
+A public [MP Library repository](https://github.com/ampl/mp) on GitHub links to a [modeling guide](https://mp.ampl.com/model-guide.html) and
+documentation of the source code. See also the slides from our presentation
+of the new interface at this summer's [EURO and ICCOPT conferences](../TALKS/2022_07_Bethlehem_Fourer.pdf).
+
+### New Solvers
+
+The first implementations using the MP interface library are
+now available in our regular distributions through the [AMPL Portal](https://portal.ampl.com/).
+
+An entirely new MP-based interface greatly expands the variety of AMPL
+expressions that can be used with the [Gurobi](https://ampl.com/products/solvers/solvers-we-sell/gurobi/) solver. The new implementation uses the solver's native "generalized
+constraints" where possible, but can be switched to use alternative
+transformations built into MP. Common univariate nonlinear functions (`exp`,
+`log`; `sin`, `cos`, `tan`) are also supported, using Gurobi's native
+piecewise-linear approximation facilities.
+
+Two relatively new linear/quadratic MIP solvers -- [COPT](https://ampl.com/products/solvers/solvers-we-sell/copt/) and [HiGHS](https://ampl.com/products/solvers/open-source/) -- are now
+also supported by AMPL, exclusively through the MP interface. Both are in
+active development and appear in recent benchmark listings. COPT, a product
+of Cardinal Operations, has joined the lineup of commercial solvers that we
+distribute. HiGHS, a free open-source solver, has evolved from a project at
+the University of Edinburgh. They appear as "copt" and "highs" in AMPL
+distributions.
+
+Currently supported MIP solvers such as [Xpress](https://ampl.com/products/solvers/solvers-we-sell/xpress/) and [CPLEX](https://ampl.com/products/solvers/solvers-we-sell/cplex/) are also planned to
+have versions with the new interface. Also we will soon be distributing the
+*MOSEK* solver with an MP interface.
+
+## Snapshot Feature (Save and Restore AMPL Sessions)
 
 In your AMPL bundle you should find `x-ampl`, the development version of AMPL where experimental features are enabled. One of such features is the snapshot command which allows saving the AMPL session in such a way that you can restore the state of AMPL using it.
 
@@ -129,80 +194,7 @@ FISH   0
 ```
 The snapshot feature is not finished and it is still being perfected. If you encounter any issues, please let us know.
 
-## Enhanced solver drivers: gurobi, copt, highs
-
-We have released `gurobi`, the enhanced
-[AMPL-Gurobi](https://ampl.com/products/solvers/solvers-we-sell/gurobi/)
-interface, `copt`, an interface to [Cardinal Optimizer](https://www.shanshu.ai/copt),
-and `highs`, an interface to [HiGHS](https://highs.dev/).
-They are included in the [AMPL distribution bundle](https://portal.ampl.com).
-
-The drivers have the following features:
-
-- Full support of logical expressions and constraints, as described in the AMPL page on Logic and Constraint Programming Extensions.
-- Algebraic expressions beyond linear and quadratic.
-- Choice between conversions in the driver vs. native solver support.
-
-[[Modeling Guide](https://mp.ampl.com/model-guide.html)] [[gurobi options](../solvers/gurobi/options.md)] [[copt options](../solvers/copt/options.md)]  [[highs options](../solvers/highs/options.md)]
-
-## New AMPL-solver interface library
-
-We're rolling out a new AMPL-solver interface library that significantly
-expands the range of model expressions that can be used with popular
-solvers. Initially, the new library is being used to implement AMPL
-interfaces to two notable new solvers, [COPT](https://ampl.com/products/solvers/solvers-we-sell/copt/) and [HiGHS](https://ampl.com/products/solvers/open-source/), and to provide
-greatly enhanced support for [Gurobi's](https://ampl.com/products/solvers/solvers-we-sell/gurobi/) generalized constraints. Extensions to
-other solvers will be released soon.
-
-### NEW SOLVER INTERFACE
-
-Modeling languages aim to let you describe
-optimization models to a computer in much the same way that you describe
-models to other people. The newly extended ["MP" interface](https://github.com/ampl/mp)
-brings AMPL closer to this goal, by allowing expanded use of a variety of convenient
-expressions in objectives and constraints. Notable examples include:
-
-- Conditional operators: `if-then-else`; `==>`, `<==`, `<==>`
-- Logical operators: `or`, `and`, `not`; `exists`, `forall`
-- Piecewise linear functions: `abs`; `min`, `max`; `<<breakpoints;slopes>>`
-- Counting operators: `count`; `atmost`, `atleast`, `exactly`; `numberof`
-- Comparison operators: `>`, `<`, `!=`; `alldiff`
-
-These operators can be applied to general forms of AMPL expressions, and
-thus can be used together in objective and constraint specifications. The
-new interface also helps solvers to accept nonlinear operators (`*`, `/`, `^`) in
-a broader variety of circumstances.
-
-A public [MP Library repository](https://github.com/ampl/mp) on GitHub links to a [modeling guide](https://mp.ampl.com/model-guide.html) and
-documentation of the source code. See also the slides from our presentation
-of the new interface at this summer's [EURO and ICCOPT conferences](https://ampl.com/MEETINGS/TALKS/2022_07_Bethlehem_Fourer.pdf), or attend
-updated presentations at the [INFORMS Annual Meeting, October 15-19](https://ampl.com/resources/informs-annual-2022/).
-
-### NEW SOLVERS
-
-The first implementations using the MP interface library are
-now available in our regular distributions through the [AMPL Portal](https://portal.ampl.com/).
-
-An entirely new MP-based interface greatly expands the variety of AMPL
-expressions that can be used with the [Gurobi](https://ampl.com/products/solvers/solvers-we-sell/gurobi/) solver. The new implementation uses the solver's native "generalized
-constraints" where possible, but can be switched to use alternative
-transformations built into MP. Common univariate nonlinear functions (`exp`,
-`log`; `sin`, `cos`, `tan`) are also supported, using Gurobi's native
-piecewise-linear approximation facilities.
-
-Two relatively new linear/quadratic MIP solvers -- [COPT](https://ampl.com/products/solvers/solvers-we-sell/copt/) and [HiGHS](https://ampl.com/products/solvers/open-source/) -- are now
-also supported by AMPL, exclusively through the MP interface. Both are in
-active development and appear in recent benchmark listings. COPT, a product
-of Cardinal Operations, has joined the lineup of commercial solvers that we
-distribute. HiGHS, a free open-source solver, has evolved from a project at
-the University of Edinburgh. They appear as "copt" and "highs" in AMPL
-distributions.
-
-Currently supported MIP solvers such as [Xpress](https://ampl.com/products/solvers/solvers-we-sell/xpress/) and [CPLEX](https://ampl.com/products/solvers/solvers-we-sell/cplex/) are also planned to
-have versions with the new interface. Also we will soon be distributing the
-*MOSEK* solver with an MP interface.
-
-## Using remote solvers from NEOS with gokestrel
+## Using Remote Solvers from NEOS with gokestrel
 
 To simplify the work of comparing and testing solvers, we have made AMPL and solver resources available online in collaboration with the [NEOS Server](https://www.neos-server.org/) project, under the auspices of the [Wisconsin Institutes for Discovery](https://www.discovery.wisc.edu/) at the University of Wisconsin, Madison. 
 

docs/source/solvers/baron/index.md

@@ -6,13 +6,12 @@ BARON is a general nonlinear optimizer capable of solving nonconvex optimization
 
 An experimental version of the driver, BARONMP, supports the extended modeling capabilities of the [MP library](https://mp.ampl.com/).
 
-[[Read More](https://ampl.com/products/solvers/solvers-we-sell/baron/)]
-[[Options](options.md)]
-[[BARONMP Options](baronmp.md)]
-[[Changes](changes.md)]
-[[BARONMP Changes](changesmp.md)]
-[[Download BARON and BARONMP](https://portal.ampl.com/user/ampl/download/baron)]
-[[Start a BARON Trial](https://portal.ampl.com/user/ampl/request/amplce/trial?solver=baron)]
+[Learn More](https://ampl.com/products/solvers/solvers-we-sell/baron/)
+| [Options](options.md)
+| [BARONMP Options](baronmp.md)
+| [Changes](changes.md)
+| [Download BARON](https://portal.ampl.com/user/ampl/download/baron)
+| [Start a BARON Trial Now!](https://portal.ampl.com/user/ampl/request/amplce/trial?solver=baron)
 
 ## How to use it
 

docs/source/solvers/bonmin/index.md

@@ -16,9 +16,9 @@ where `f(x): R^n --> R`, `g(x): R^n --> R^m` are twice continuously differentiab
 
 The algorithms in Bonmin are exact when the functions `f` and `g` are convex; in the case where `f` or `g` or both are non-convex they are heuristics.
 
-[[Read More](https://ampl.com/products/solvers/open-source-solvers/)]
-[[Options](#solver-options)]
-[[Download BONMIN](https://portal.ampl.com/user/ampl/download/coin)]
+[Learn More](https://ampl.com/products/solvers/open-source-solvers/)
+| [Options](#solver-options)
+| [Download BONMIN](https://portal.ampl.com/user/ampl/download/coin)
 
 ## How to use it
 
@@ -74,8 +74,11 @@ The algorithms in Bonmin are exact when the functions `f` and `g` are convex; in
 
 ## Resources
 
-* [Solver options](#solver-options)
-* [Solve result codes](#retrieving-solutions)
+- [BONMIN](#bonmin)
+  - [How to use it](#how-to-use-it)
+  - [Resources](#resources)
+  - [Solver options](#solver-options)
+  - [Retrieving solutions](#retrieving-solutions)
 
 ## Solver options
 

docs/source/solvers/cbc/index.md

@@ -6,11 +6,11 @@ The [COIN Branch and Cut solver (CBC)](https://github.com/coin-or/Cbc) is an ope
 The framework used by the driver supports automatic reformulation for many expression types; the modeling guide can be
 found [here](https://mp.ampl.com/model-guide.html).
 
-[[Read More](https://ampl.com/products/solvers/open-source-solvers/)]
-[[Modeling guide](https://mp.ampl.com/model-guide.html)]
-[[Options](#solver-options)]
-[[Changes](changes.md)]
-[[Download CBC](https://portal.ampl.com/user/ampl/download/cbc)]
+[Learn More](https://ampl.com/products/solvers/open-source-solvers/)
+| [Modeling guide](https://mp.ampl.com/model-guide.html)
+| [Options](#solver-options)
+| [Changes](changes.md)
+| [Download CBC](https://portal.ampl.com/user/ampl/download/cbc)
 
 ## How to use it
 

docs/source/solvers/conopt/index.md

@@ -4,11 +4,11 @@
 
 A proven choice for highly nonlinear problems, CONOPT’s efficient and reliable multi-method architecture handles a broad range of models. Specialized techniques achieve feasibility quickly, while powerful preprocessing tools reduce problem size and suggest formulation improvements.
 
-[[Read More](https://ampl.com/products/solvers/solvers-we-sell/conopt/)]
-[[Options](options.md)]
-[[Changes](changes.md)]
-[[Download CONOPT](https://portal.ampl.com/user/ampl/download/conopt)]
-[[Start a CONOPT Trial](https://portal.ampl.com/user/ampl/request/amplce/trial?solver=conopt)]
+[Learn More](https://ampl.com/products/solvers/solvers-we-sell/conopt/)
+| [Options](options.md)
+| [Changes](changes.md)
+| [Download CONOPT](https://portal.ampl.com/user/ampl/download/conopt)
+| [Start a CONOPT Trial Now!](https://portal.ampl.com/user/ampl/request/amplce/trial?solver=conopt)
 
 ## How to use it
 

docs/source/solvers/copt/index.md

@@ -10,12 +10,12 @@ The framework used by the driver supports automatic reformulation for many expre
 found [here](https://mp.ampl.com/model-guide.html).
 
 
-[[Read More](https://ampl.com/products/solvers/solvers-we-sell/copt/)]
-[[Modeling guide](https://mp.ampl.com/model-guide.html)]
-[[Options](#solver-options)]
-[[Changes](changes.md)]
-[[Download COPT](https://portal.ampl.com/user/ampl/download/copt)]
-[[Start a COPT Trial](https://portal.ampl.com/user/ampl/request/amplce/trial?solver=copt)]
+[Learn More](https://ampl.com/products/solvers/solvers-we-sell/copt/)
+| [Modeling guide](https://mp.ampl.com/model-guide.html)
+| [Options](#solver-options)
+| [Changes](changes.md)
+| [Download COPT](https://portal.ampl.com/user/ampl/download/copt)
+| [Start a COPT Trial Now!](https://portal.ampl.com/user/ampl/request/amplce/trial?solver=copt)
 
 ## How to use it
 

docs/source/solvers/couenne/index.md

@@ -4,9 +4,9 @@
 
 The [COIN Couenne solver (COUENNE, Convex Over and Under ENvelopes for Nonlinear Estimation)](https://github.com/coin-or/Couenne) is a spatial branch & bound algorithm that implements linearization, bound reduction, and branching techniques for Mixed-integer, Nonlinear Programming (MINLP) problems. The purpose of Couenne is to find global optima of nonconvex MINLPs.
 
-[[Read More](https://ampl.com/products/solvers/open-source-solvers/)]
-[[Options](#solver-options)]
-[[Download COUENNE](https://portal.ampl.com/user/ampl/download/coin)]
+[Learn More](https://ampl.com/products/solvers/open-source-solvers/)
+| [Options](#solver-options)
+| [Download COUENNE](https://portal.ampl.com/user/ampl/download/coin)
 
 ## How to use it
 
@@ -62,8 +62,11 @@ The [COIN Couenne solver (COUENNE, Convex Over and Under ENvelopes for Nonlinear
 
 ## Resources
 
-* [Solver options](#solver-options)
-* [Solve result codes](#retrieving-solutions)
+- [COUENNE](#couenne)
+  - [How to use it](#how-to-use-it)
+  - [Resources](#resources)
+  - [Solver options](#solver-options)
+  - [Retrieving solutions](#retrieving-solutions)
 
 ## Solver options
 

docs/source/solvers/cplex/index.md

@@ -4,11 +4,11 @@
 
 IBM ILOG CPLEX has been a well known and widely used large-scale solver for over three decades. Its efficiency and robustness have been demonstrated through varied applications in thousands of commercial installations worldwide.
 
-[[Read More](https://ampl.com/products/solvers/solvers-we-sell/cplex/)]
-[[Options](#solver-options)]
-[[Changes](changes.md)]
-[[Download CPLEX](https://portal.ampl.com/user/ampl/download/cplex)]
-[[Start a CPLEX Trial](https://portal.ampl.com/user/ampl/request/amplce/trial?solver=cplex)]
+[Learn More](https://ampl.com/products/solvers/solvers-we-sell/cplex/)
+| [Options](#solver-options)
+| [Changes](changes.md)
+| [Download CPLEX](https://portal.ampl.com/user/ampl/download/cplex)
+| [Start a CPLEX Trial Now!](https://portal.ampl.com/user/ampl/request/amplce/trial?solver=cplex)
 
 ## How to use it
 

docs/source/solvers/gcg/index.md

@@ -8,11 +8,11 @@ branch-price-and-cut algorithm to solve it to optimality. Alternatively,
 GCG is able to automatically apply a Benders decomposition.
 No user interaction is necessary, thus GCG provides decomposition-based MIP solving technology to everyone.
 
-[[Read More](https://ampl.com/products/solvers/open-source-solvers/)]
-[[GCG modeling guide](#gcg-modeling-guide)]
-[[Options](#solver-options)]
-[[Changes](changes.md)]
-[[Download GCG](https://portal.ampl.com/user/ampl/download/gcg)]
+[Learn More](https://ampl.com/products/solvers/open-source-solvers/)
+| [GCG modeling guide](#gcg-modeling-guide)
+| [Options](#solver-options)
+| [Changes](changes.md)
+| [Download GCG](https://portal.ampl.com/user/ampl/download/gcg)
 
 ## How to use it