OptaPlanner Training Courses

OptaPlanner Training

OptaPlanner - constraint satisfaction solver courses

OptaPlanner Course Outlines

Code Name Duration Overview
optaprac OptaPlanner in Practice 21 hours This course uses a practical approach to teaching OptaPlanner. It provides participants with the tools needed to perform the basic functions of this tool. 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

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Course Discounts

Course Venue Course Date Course Price [Remote / Classroom]
Puppet Advanced Reading TVP Tue, 2017-12-19 09:30 £2970 / £3765
Docker for Developers and System Administrators Bristol, Temple Gate Wed, 2018-01-10 09:30 £1980 / £2580
Corporate Governance Edinburgh Fri, 2018-02-02 09:30 £1089 / £1739
Statistics Level 1 Swansea- Princess House Thu, 2018-03-29 09:30 £1980 / £2280
Comprehensive Git Sheffield Tue, 2018-04-24 09:30 £2970 / £3570

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