update algo. count

SimonBlanke · SimonBlanke · commit 0798f34d2793 · 2026-04-18T20:46:05.000+02:00
diff --git a/docs/source/about.rst b/docs/source/about.rst
@@ -30,7 +30,7 @@ Mission
 ^^^^^^^
 
 GFO aims to make gradient-free optimization accessible and practical. By providing
-a unified interface across 22 algorithms, it reduces the complexity of choosing
+a unified interface across 23 algorithms, it reduces the complexity of choosing
 and switching between optimization methods. The library prioritizes simplicity,
 transparency, and reliability.
 
diff --git a/docs/source/faq/index.rst b/docs/source/faq/index.rst
@@ -11,7 +11,7 @@ General
 GFO focuses on simplicity and transparency:
 
 - Search spaces are just NumPy arrays (no special types)
-- All 22 algorithms share the same interface
+- All 23 algorithms share the same interface
 - Pure Python with minimal dependencies
 - Serves as the backend for Hyperactive
 
diff --git a/docs/source/get_started/dependencies.rst b/docs/source/get_started/dependencies.rst
@@ -38,7 +38,7 @@ This adds:
   for surrogate models
 
 However, sklearn is **not required**. GFO ships its own Gaussian Process, Random
-Forest, and KDE implementations, so all 22 optimizers work out of the box without
+Forest, and KDE implementations, so all 23 optimizers work out of the box without
 scikit-learn installed.
 
 
diff --git a/docs/source/get_started/index.rst b/docs/source/get_started/index.rst
@@ -23,7 +23,7 @@ running your first optimization.
         :link: algorithms
         :link-type: doc
 
-        Overview of all 22 algorithms organized by category: local, global,
+        Overview of all 23 algorithms organized by category: local, global,
         population-based, and sequential model-based.
 
     .. grid-item-card:: Mixed Search Spaces
diff --git a/docs/source/index.rst b/docs/source/index.rst
@@ -316,7 +316,7 @@ for Python.
         Perfect when you need fine-grained control over the
         optimization process.
 
-        - 22 algorithms
+        - 23 algorithms
         - NumPy-based search spaces
         - Constraint support
 
@@ -375,7 +375,7 @@ Documentation
         :link-type: doc
         :text-align: center
 
-        All 22 optimization algorithms explained
+        All 23 optimization algorithms explained
 
     .. grid-item-card:: Examples
         :link: examples
diff --git a/docs/source/user_guide.rst b/docs/source/user_guide.rst
@@ -73,7 +73,7 @@ Every optimization in GFO involves three components:
 
       **How to optimize**
 
-      The algorithm that explores your search space. Choose from 22 algorithms
+      The algorithm that explores your search space. Choose from 23 algorithms
       across local search, global search, population methods, and SMBO.
 
    .. grid-item-card:: Objective Functions
