MTH3330
Optimisation and operations research
基本信息
| 学分 | 6 credit points |
|---|---|
| 开课学期 | First semester |
| 校区 | Malaysia |
| 考核构成 | Final assessment - Exam (3 hours and 10 minutes) — 50% Continuous assessment — 50% |
开课安排1 条
| 教学期 | 授课方式 | 状态 |
|---|---|---|
| First semester | Teaching activities are on-campus (ON-CAMPUS) | 开课 |
以上为该校区在官方资料中登记的全部开课安排，不是汇总。同一门课可能在多个 教学期开课，也可能不同教学期的授课方式不同。
课程简介
This unit introduces some of the fundamental concepts and algorithms of mathematical optimisation. Optimisation underpins many parts of both data analytics (machine learning) and business analytics (management science/operations research). The concepts and approaches taught in this unit will be illustrated using examples from both types of analytics, such as training ML models and planning models arising in supply chain optimisation. The unit provides an introduction to the mathematics of continuous optimisation with focus on iterative gradient descent methods, linear programming and network optimisation. It covers both the underpinning theory, such as convergence analysis and duality, and the practical implementation of optimisation algorithms.
以上为 Monash Handbook 的官方原文，版权属 Monash University，此处按本站要求转载并标注出处： 官方页面 ↗
学习成果4 条
官方原文（Learning outcomes），版权属 Monash University。
- ULO1 Explain and apply the mathematical theory of optimisation, including optimality conditions, iterative algorithms for nonlinear problems, and the principles of duality and non-smooth optimisation;
- ULO2 Formulate and analyse optimisation problems arising in machine learning, operations research, and network optimisation, selecting and justifying appropriate algorithms;
- ULO3 Implement and evaluate linear programming and related optimisation algorithms, proving optimality where appropriate and applying them to real-world data and applications;
- ULO4 Communicate optimisation reasoning and results effectively, both orally and in writing, and collaborate in small groups to solve problems.
教学方式与预期工作量
教学方式
Active learning - Active learning will occur in lectures and applied classes.
预期工作量
• Two 1.5-hour workshops;
• One 2-hour applied class (in weeks 2-12) and
• 7 hours of independent study per week.
官方原文，版权属 Monash University。
先修 / 同修要求
官方资料未列出该课程的先修要求。
先修链路
官方资料未列出该课程的先修要求，因此没有链路可画。
属于这些学位1 个
这门课出现在下列学位的官方结构里。反过来说：如果你读的是这些学位之一，它大概率是要修的 （必修还是选修取决于它在 Part 里的位置，点进去看结构）。
数据来源
- 数据来源
- 官方网页
handbook.monash.edu ↗ - 抓取时间
- 2026-09-13
- 可信度
- 程序抓取，未人工核实
查看官方完整描述 ↗ — 事实性字段（代码、学分、教学期、授课方式、考核权重、先修/同修/互斥关系）与 课程简介、学习成果、教学方式、预期工作量均取自官方 Handbook； 正文版权属 Monash University，此处转载并逐处标注出处。
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