啟發式解法
Heuristics
| 節 | 週二 |
|---|---|
5 13:20–14:10 | 啟發式解法 A905（光復） 3 節連堂 |
6 14:20–15:10 | |
7 15:30–16:20 |
* 根據陽明交大上課時間表所列
This course would like to introduce several Softcomputing heuristics that shall be able to solve the difficult problems in Transportation and Logistics Management. We shall use several classical optimization problems as platforms to introduce the implementation of these heuristics, the theoretical foundations and the guidelines (e.g., the parameter settings, etc) for the application of these heuristics.
Basic programming skill and elementary level of probability theory.
無備註
The teaching of this course shall be mostly conducted by lecturing. Also, we will employ many sets of homework to assist the students to get used to the application of the heuristics.
1. Homework 30% 2. Midterm examine 40% 3. Term project presentation 30%
Fundamentals of Algorithm Design and Complexity Analysis.
1. The Fundamentals of Algorithm Design 2. Introduction to Complexity Analysis
- 講授：
- 3
Design of Local Search
1. The Traveling Salesman Problem 2. Local search procedure for solving TSP 3. Greedy algorithms
- 講授：
- 3
Simulated Annealing (SA)
1. Introduction of the SA 2. Theoretical Background of SA 3. Application of SA: Graph Partitioning Problem 4. Optimizing the Parameter Setting in Simulated Annealing
- 講授：
- 9
Genetic Algorithm (GA)
1. Introduction of the GA 2. Theoretical Background of Genetic Algorithm using Binary Encoding 3. Hybrid GA with local search procedures 4. Applying GA for Solving Constrained Optimization Problems
- 講授：
- 12
Tabu Search (TS)
1. Introduction of the TS 2. Optimizing the Parameter Setting in TS 3. Optimality equations and the principle of optimality 4. Application of TS in Transportation and Logistics Management
- 講授：
- 9
Stochastic Global Optimization Techniques
1. The Electromagnetic Method and its convergence analysis 2. A Tropical Cyclone-based Method 3. The Particle Swarm Optimization Algorithm
- 講授：
- 6
Computational Experiments with Heuristic Methods
Designing and Reporting on Computational Experiments with Heuristic Methods
- 講授：
- 3
| 週次 | 主題 |
|---|---|
| 第 1 週 | Fundamentals of Algorithm Design and Complexity Analysis. 9/10 |
| 第 2 週 | Design of Local Search Algorithms and Greedy Algorithms. 9/17 |
| 第 3 週 | Introduction of the Simulated Annealing and Theoretical Background of Simulated Annealing 9/24 |
| 第 4 週 | Application of Simulated Annealing: Graph Partitioning Problem 10/1 |
| 第 5 週 | Optimizing the Parameter Setting in Simulated Annealing 10/8 |
| 第 6 週 | Introduction of the Genetic Algorithm 10/15 |
| 第 7 週 | The Theoretical Background of Genetic Algorithm using Binary Encoding 10/22 |
| 第 8 週 | The Genetic Algorithm using Integer Encoding 10/29 |
| 第 9 週 | Hybrid Genetic Algorithm with local search procedures Applying Genetic Algorithm for Solving Constrained Optimization Problems 11/5 |
| 第 10 週 | Midterm Examine 11/12 |
| 第 11 週 | Introduction of the Tabu Search 11/19 |
| 第 12 週 | Optimizing the Parameter Setting in Tabu Search 11/26 |
| 第 13 週 | Application of Tabu search in Transportation and Logistics Management: the truck and trailer routing problem 12/3 |
| 第 14 週 | Stochastic Global Optimization Techniques: The Electromagnetic Method and its convergence analysis 12/10 |
| 第 15 週 | Stochastic Global Optimization Techniques: A Tropical Cyclone-based Method and the Particle Swarm Optimization Algorithm 12/17 |
| 第 16 週 | Designing and Reporting on Computational Experiments with Heuristic Methods 12/24 |
| 第 17 週 | Term project presentation 12/31 |
| 第 18 週 | Term project presentation 1/7 |
1. The lecture notes prepared by Prof. Yao. 2. The journal papers related to the introduced Softcomputing heuristics.
- 地點
- A809
- 時間
- MON G THU AB
- 聯絡方式
- ext: 57215 myao@mail.nctu.edu.tw