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The following commit(s) were added to refs/heads/asf-site by this push:
new a41b595 Updated to OptaPlanner 10.0.0 and Timefold 1.16.0
a41b595 is described below
commit a41b59583345d2eb77b74980dae7d570cca28da9
Author: Paul King <[email protected]>
AuthorDate: Tue Dec 10 18:20:44 2024 +1000
Updated to OptaPlanner 10.0.0 and Timefold 1.16.0
---
...lving-simple-optimization-problems-with-groovy.adoc | 18 +++++++++++++-----
1 file changed, 13 insertions(+), 5 deletions(-)
diff --git
a/site/src/site/blog/solving-simple-optimization-problems-with-groovy.adoc
b/site/src/site/blog/solving-simple-optimization-problems-with-groovy.adoc
index d08764e..50e289d 100644
--- a/site/src/site/blog/solving-simple-optimization-problems-with-groovy.adoc
+++ b/site/src/site/blog/solving-simple-optimization-problems-with-groovy.adoc
@@ -171,7 +171,7 @@ The naming possibly deserves some explanation. There has
been ongoing
effort to modularise Commons Math and there are numerous components
delivered as a result. The optimisation classes haven't
been worked on yet and are available in the aforementioned artifact.
-* Using `org.hipparchus:hipparchus-optim:3.0` gives classes from the forked
+* Using `org.hipparchus:hipparchus-optim:3.1` gives classes from the forked
project. For the classes we are using, there is essentially no difference
in the fork, but other parts of the library have seen useful updates
if you don't mind having a dependency that isn't backed by the ASF.
@@ -205,7 +205,7 @@ OptaPlanner is an optimization library combining
optimization algorithms with co
For most of the last 10 years the library was developed under Red Hat's
guidance.
In the last 12 months, the project and other related projects
were donated to the https://www.apache.org/[ASF] as part of
https://kie.apache.org/[Apache KIE].
-More recently, the library was forked as
+More recently, the library was also forked as
https://timefold.ai/[Timefold].
In this blog, we'll use Timefold, but the code in the examples remains the
same for both libraries as you can see in the
@@ -342,7 +342,8 @@ class DietConstraintProvider implements ConstraintProvider {
.asConstraint("Max $foodName")
}
- private static ToIntFunction<Food> totalCost = f -> (f.cost *
f.amount).toInteger()
+ private static ToIntFunction<Food> totalCost = f ->
+ (f.cost * f.amount).toInteger()
private static Constraint minCost(ConstraintFactory factory) {
factory.forEach(Food)
@@ -411,12 +412,14 @@ along with the updated `config` definition:
[source,groovy]
----
-def construction = new
ConstructionHeuristicPhaseConfig(constructionHeuristicType: FIRST_FIT)
+def construction = new ConstructionHeuristicPhaseConfig(
+ constructionHeuristicType: FIRST_FIT)
def moveSelector = new UnionMoveSelectorConfig([
new ChangeMoveSelectorConfig(),
new SwapMoveSelectorConfig()
])
-def localSearch = new LocalSearchPhaseConfig(localSearchType:
VARIABLE_NEIGHBORHOOD_DESCENT,
+def localSearch = new LocalSearchPhaseConfig(
+ localSearchType: VARIABLE_NEIGHBORHOOD_DESCENT,
moveSelectorConfig: moveSelector)
def config = new SolverConfig()
.withSolutionClass(DietSolution)
@@ -459,3 +462,8 @@ libraries to solve a diet case study. Our main focus was the
Apache Commons Math and Hipparchus libraries.
We also explored using the more powerful Timeflow and OptaPlanner
libraries.
+
+.Update history
+****
+*10/Dec/2024*: Updated to OptaPlanner 10.0.0 and Timefold 1.16.0.
+****
