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mkhraijah · Dec 9, 2022 · 791d84f · 791d84f
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diff --git a/README.md b/README.md
@@ -22,10 +22,7 @@ The current version of `PowerModelsADA` implements four distributed algorithms:
 - Auxiliary Problem Principle (APP)
 - Augmented Lagrangian Alternating Direction Inexact Newton (ALADIN)
 
-`PowerModelsADA` can be extended to include variations of the existing algorithms or new user-defined algorithms. 
-
-<!--
- More details about the formulations and algorithm implementations are shown in [Technical Specifications](https://mkhraijah.github.io/PowerModelsADA.jl/dev/specification/)
+`PowerModelsADA` can be extended to include variations of the existing algorithms or new user-defined algorithms. More details about the formulations and algorithm implementations are shown in [Technical Specifications](https://mkhraijah.github.io/PowerModelsADA.jl/dev/specification/)
 
 ## Installation
 
@@ -34,10 +31,7 @@ The current version of `PowerModelsADA` implements four distributed algorithms:
 ```julia
 using Pkg
 Pkg.add("PowerModelsADA")
-```  
--->
-
-
+```
 
 ## Examples
 

diff --git a/docs/src/index.md b/docs/src/index.md
@@ -11,16 +11,23 @@ CurrentModule = PowerModelsADA
 ## Distributed Algorithms 
 The `PowerModelsADA` framework is designed to easily incorporate new alternating distributed algorithms. The framework provides means to decompose a test case into multiple areas, model the subproblems associated with each area using `PowerModels`, solve the supropblems in parallel using multi-threading, communicate the shared data between the areas, and calculate the mismatches to decide if the termination criteria are satisfied.
 
-
 The current version of `PowerModelsADA` implements four distributed algorithms: 
 
 - Alternating Direction Method of Multipliers (ADMM)
 - Analytical Target Cascading (ATC)
 - Auxiliary Problem Principle (APP)
 - Augmented Lagrangian Alternating Direction Inexact Newton (ALADIN)
 
-`PowerModelsADA` can be extended to include variations of the existing algorithms or new user-defined algorithms. 
+`PowerModelsADA` can be extended to include variations of the existing algorithms or new user-defined algorithms. More details about the formulations and algorithm implementations are shown in [Technical Specifications](https://mkhraijah.github.io/PowerModelsADA.jl/dev/specification/)
+
+## Installation
 
+`PowerModelsADA` can be installed using the Julia package manager with
+
+```julia
+using Pkg
+Pkg.add("PowerModelsADA")
+```
 
 ## Examples