OptaPlanner in Practice Training Course

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Course Code

optaprac

Duration Duration

21 hours (usually 3 days including breaks)

Requirements Requirements

Overview Overview

Course Outline Course Outline

Planner introduction

  • What is OptaPlanner?
  • What is a planning problem?
  • Use Cases and examples

Bin Packaging Problem Example

  • Problem statement
  • Problem size
  • Domain model diagram
  • Main method
  • Solver configuration
  • Domain model implementation
  • Score configuration

Travelling Salesman Problem (TSP)

  • Problem statement
  • Problem size
  • Domain model
  • Main method
  • Chaining
  • Solver configuration
  • Domain model implementation
  • Score configuration

Planner configuration

  • Overview
  • Solver configuration
  • Model your planning problem
  • Use the Solver

Score calculation

  • Score terminology
  • Choose a Score definition
  • Calculate the Score
  • Score calculation performance tricks
  • Reusing the Score calculation outside the Solver

Optimization algorithms

  • Search space size in the real world
  • Does Planner find the optimal solution?
  • Architecture overview
  • Optimization algorithms overview
  • Which optimization algorithms should I use?
  • SolverPhase
  • Scope overview
  • Termination
  • SolverEventListener
  • Custom SolverPhase

Move and neighborhood selection

  • Move and neighborhood introduction
  • Generic Move Selectors
  • Combining multiple MoveSelectors
  • EntitySelector
  • ValueSelector
  • General Selector features
  • Custom moves

Construction heuristics

  • First Fit
  • Best Fit
  • Advanced Greedy Fit
  • Cheapest insertion
  • Regret insertion

Local search

  • Local Search concepts
  • Hill Climbing (Simple Local Search)
  • Tabu Search
  • Simulated Annealing
  • Late Acceptance
  • Step counting hill climbing
  • Late Simulated Annealing (experimental)
  • Using a custom Termination, MoveSelector, EntitySelector, ValueSelector or Acceptor

Evolutionary algorithms

  • Evolutionary Strategies
  • Genetic Algorithms

Hyperheuristics

Exact methods

  • Brute Force
  • Depth-first Search

Benchmarking and tweaking

  • Finding the best Solver configuration
  • Doing a benchmark
  • Benchmark report
  • Summary statistics
  • Statistics per dataset (graph and CSV)
  • Advanced benchmarking

Repeated planning

  • Introduction to repeated planning
  • Backup planning
  • Continuous planning (windowed planning)
  • Real-time planning (event based planning)

Drools

  • Short introduction to Drools
  • Writing Score Function in Drools

Integration

  • Overview
  • Persistent storage
  • SOA and ESB
  • Other environment

Public Classroom Public Classroom
Participants from multiple organisations. Topics usually cannot be customised
From 2510EUR
(3)
Private Classroom Private Classroom
Participants are from one organisation only. No external participants are allowed. Usually customised to a specific group, course topics are agreed between the client and the trainer.
Private Remote Private Remote
The instructor and the participants are in two different physical locations and communicate via the Internet
From 2680EUR
Request quote

The more delegates, the greater the savings per delegate. Table reflects price per delegate and is used for illustration purposes only, actual prices may differ.

Number of Delegates Public Classroom Private Remote
1 2510EUR 2680EUR
2 1680EUR 1740EUR
3 1403EUR 1427EUR
4 1265EUR 1270EUR
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Upcoming Courses

VenueCourse DateCourse Price [Remote / Classroom]
BaselTue, 2016-12-27 09:302680EUR / 3330EUR
BernWed, 2016-12-28 09:302680EUR / 3330EUR

Course Discounts

Course Venue Course Date Course Price [Remote / Classroom]
WildFly Server Administration Bern Thu, 2016-12-15 09:30 2495EUR / 2995EUR

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