From 871d6c2e5ef493988d8826d7f9e6f38b5ff35970 Mon Sep 17 00:00:00 2001 From: Oscar Dowson Date: Fri, 14 Jun 2024 09:37:19 +1200 Subject: [PATCH] [docs] update should_i_use.md --- docs/src/should_i_use.md | 16 +++++++--------- 1 file changed, 7 insertions(+), 9 deletions(-) diff --git a/docs/src/should_i_use.md b/docs/src/should_i_use.md index 99e71844966..28ef5e58217 100644 --- a/docs/src/should_i_use.md +++ b/docs/src/should_i_use.md @@ -8,11 +8,12 @@ you should _not_ use JuMP. ## When should you use JuMP? -You should use JuMP if you have a constrained optimization problem for which you -can formulate using the language of mathematical programming, that is: +You should use JuMP if you have a constrained optimization problem that is +formulated using the language of mathematical programming, that is, the problem +has: - * a set of decision variables - * a scalar- or vector-valued objective function + * a set of real- or complex-valued decision variables + * a scalar- or vector-valued real objective function * a set of constraints. Key reasons to use JuMP include: @@ -30,9 +31,7 @@ Key reasons to use JuMP include: - Ease of embedding - JuMP itself is written purely in Julia. Solvers are the only binary dependencies. - - JuMP provides automatic installation of many open-source solvers. This is - different to modeling languages in Python which require you to download - and install a solver yourself. + - JuMP provides automatic installation of most solvers. - Because it is embedded in a general-purpose programming language, JuMP makes it easy to solve optimization problems as part of a larger workflow, for example, inside a simulation, behind a web server, or as a subproblem @@ -47,8 +46,7 @@ Key reasons to use JuMP include: - JuMP communicates with most solvers in memory, avoiding the need to write intermediary files. - Access to advanced algorithmic techniques - - JuMP supports efficient _in-memory_ re-solves of linear programs, which - previously required using solver-specific or low-level C++ libraries. + - JuMP supports efficient _in-memory_ re-solves of models. - JuMP provides access to solver-independent and solver-dependent [Callbacks](@ref callbacks_manual).