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This is similar for Gradle, Ivy and Buildr. If you use Maven, add a dependency to optaplanner-core in your project's The OptaPlanner jars are also available in the central maven repository (and also in With Planner, it is easy to switch the optimizationĪlgorithm, by changing the solver configuration in a few lines of XML or code.ġ.3.3. Use OptaPlanner with Maven, Gradle, Ivy, Buildr or ANT Depending on the use case, some optimization algorithms perform better than others,īut it's impossible to tell in advance. OptaPlanner supports several optimization algorithms to efficiently wade through that incredibly large Implementation is forced to evaluate at least a subset of all those possible solutions. Because there is no silver bullet to find the optimal solution, any As you can see in the examples, most instances have a lot more possible solutions than the minimal number The best solution found is likely to be feasible and, given enoughĬounterintuitively, the number of possible solutions is huge (if calculated correctly), even with a smallĭataset. Implementation in a given amount of time.

The best solution found is the solution with the highest score found by an There is always at least 1 optimal solution, even in the case that thereĪre no feasible solutions and the optimal solution isn't feasible. Every feasible solution is a possible solution.Īn optimal solution is a solution with the highest score. Sometimes there are no feasible solutions. The number of feasible solutions tends to be relative to the number of possible solutions. Many of thoseĪ feasible solution is a solution that does not break any (negative) hardĬonstraints. Planning problems tend to have an incredibly large number of possible solutions. A possible solution is any solution, whether or not it breaks any number ofĬonstraints.

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