视频教程：Python 运筹学与优化项目 (英文)

视频教程：Python 运筹学与优化项目

发布日期：2024 年 5 月

• 制作单位：Advancedor Academy
• 格式：MP4
• 视频分辨率：1280×720
• 音频：AAC，44.1 KHz，2 通道
• 类型：在线学习
• 语言：英语
• 时长：124 讲（7 小时 1 分钟）
• 大小：3 GB

课程内容

掌握优化技术：从线性规划到机器学习增强算法

主要收获

通过本课程，你将学到：

• 掌握使用 Python 优化供应链和工厂运营。
• 构建 Python 模型，有效规划人力资源并优化网络流程。
• 利用 Python 库进行调度、路由和库存管理模拟。
• 使用基于 Python 的算法解决复杂的设施位置和容量问题。
• 利用 Python 进行高级运筹学技术，如随机过程、博弈论和动态规划。
• 集成多目标决策工具，增强运营策略。
• 实施鲁棒的优化和随机模型，管理运营中的不确定性。

先决条件

• 需要基本的 Python 编程能力。
• 熟悉运营管理基本概念有益但不是必需的。
• 具备基本的数学技能，包括代数和入门统计学。

课程描述

欢迎来到这个全面的运筹学与优化课程，在这里你将掌握一系列解决复杂实际问题所必需的优化技术。无论你是刚刚开始还是经验丰富的专业人士，希望扩展你在高级算法方面的知识，本课程都提供了有价值的见解和实用技能。

在整个课程中，我们将涵盖关键主题，如线性规划、离散优化和随机过程。你还将探索包括机器学习增强的优化算法、遗传算法和多目标决策在内的复杂领域。每个模块都旨在逐步建立你的理解，提供直接适用于实际场景的实例和互动练习。

我们将审视特定应用，如优化供应链、收入管理中的动态规划以及解决调度问题。你将学会使用 Python 中流行的工具和库，如 Gurobi、SciPy、PuLP、Or-Tools，从而掌握在项目中有效实施这些技术的技能。

此外，课程还包括来自制造业、医疗保健和物流等行业的案例研究，提供了运筹学如何应用于优化各种运营方面的背景。通过本课程，你将具备分析复杂系统、设计优化策略并有效应用各种优化算法的能力。

加入我一起探索运筹学和优化的潜力。你将不仅在理论方面有更深入的理解，还将具备将这些知识应用于提高决策和效率的能力，无论是在职业生涯还是学术追求中。

本课程适合希望在运筹学领域建立扎实基础、提高分析能力并学习系统化方法解决优化问题的任何人。

Operations Research & Optimization Projects With Python

Published 5/2024
Created by Advancedor Academy
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 124 Lectures ( 7h 1m ) | Size: 3 GB

Mastering Optimization Techniques: From Linear Programming to Machine Learning-Enhanced Algorithms

What you’ll learn:
Master the use of Python for optimizing supply chains and factory operations.
Build Python models to plan manpower effectively and optimize network flows.
Leverage Python libraries for scheduling, routing, and inventory management simulations.
Solve complex facility location and capacity problems using Python-based algorithms.
Utilize Python for advanced operations research techniques like stochastic processes, game theory, and dynamic programming.
Integrate multi-objective decision-making tools for enhanced operational strategies.
Implement robust optimization and stochastic models to manage uncertainty in operations.

Requirements:
Basic proficiency in Python programming is required.
Familiarity with fundamental concepts in operations management is beneficial but not required.
Basic mathematical skills, including algebra and introductory statistics.

Description:
Welcome to this comprehensive course on Operations Research and Optimization, where you will master a range of optimization techniques essential for solving complex real-world problems. Whether you are starting out or an experienced professional looking to expand your knowledge in advanced algorithms, this course offers valuable insights and practical skills.Throughout this course, we will cover key topics such as linear programming, discrete optimization, and stochastic processes. You will also explore sophisticated areas including machine learning-enhanced optimization algorithms, genetic algorithms, and multi-objective decision making. Each module is designed to gradually build your understanding, with practical examples and interactive exercises that directly apply to real-life scenarios.We’ll examine specific applications such as optimizing supply chains, dynamic programming in revenue management, and solving scheduling problems. You’ll learn to use popular tools and libraries in Python, such as Gurob,SciPy, PuLP, Or-Tools equipping you with the skills to effectively implement these techniques in your projects.Moreover, the course includes case studies from industries like manufacturing, healthcare, and logistics, providing context on how operations research is applied to optimize various operational aspects. By the end of this course, you will be equipped to analyze complex systems, design optimization strategies, and apply various optimization algorithms effectively.Join me in this exploration to unlock the potential of operations research and optimization. You will finish this course not only with a deeper understanding of the theoretical aspects but also with the capability to apply this knowledge to enhance decision-making and efficiency in your professional life or academic pursuits.This course is ideal for anyone who wishes to build a solid foundation in operations research, improve their analytical skills, and learn systematic approaches to tackle optimization problems.

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