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开课地址:【上海】同济大学(沪西)/新城金郡商务楼(11号线白银路站)【深圳分部】:电影大厦(地铁一号线大剧院站) 【武汉分部】:佳源大厦【成都分部】:领馆区1号【沈阳分部】:沈阳理工大学【郑州分部】:锦华大厦【石家庄分部】:瑞景大厦【北京分部】:北京中山学院 【南京分部】:金港大厦
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课程大纲 |
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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
the 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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