 班级规模及环境--热线:4008699035 手机:15921673576( 微信同号) |
|
坚持小班授课，为保证培训效果，增加互动环节，每期人数限3到5人。 |
| 上课时间和地点 |
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 【南京分部】：金港大厦
新开班 (连续班 、周末班、晚班）：2024年12月30日......(欢迎您垂询，视教育质量为生命！) |
| 实验设备 |
☆资深工程师授课
☆注重质量
☆边讲边练
☆合格学员免费推荐工作
★实验设备请点击这儿查看★ |
| 质量保障 |
1、培训过程中，如有部分内容理解不透或消化不好，可免费在以后培训班中重听；
2、课程完成后,授课老师留给学员手机和Email,保障培训效果,免费提供半年的技术支持。
3、培训合格学员可享受免费推荐就业机会。 |
课程大纲 |
| |
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
|
首页 课程表 在线聊 报名 讲师 品牌 QQ聊 活动 就业