|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/optimization-with-python-linear-nonlinear-and-cplex-gurobi/
课程评论：没有评论
课程名称：使用Python优化：解决运筹学问题 课程概述：近年来，企业的运营规划和长期规划变得愈加复杂。信息瞬息万变，决策过程充满挑战。因此，优化算法（即运筹学）被用来寻找问题的最佳解决方案。这个领域的专业人士在市场上备受重视。在本课程中，您将学习如何应用数学优化和元启发式算法来解决问题，包括： - 线性规划（LP） - 混合整数线性规划（MILP） - 非线性规划（NLP） - 混合整数非线性规划（MINLP） - 遗传算法（GA） - 多目标优化问题与NSGA-II（简介） - 粒子群算法（PSO） - 约束编程（CP） - 二阶锥规划（SCOP） - 非凸二次规划（QP） 此外，还将探索以下求解器和框架： - 求解器：CPLEX、Gurobi、GLPK、CBC、IPOPT、Couenne、SCIP - 框架：Pyomo、Or-Tools、PuLP、Pymoo 您还将使用遗传算法、Pyswarm、Numpy、Pandas、Matplotlib等工具和包来解决问题。此外，课程中将介绍在使用二进制变量时的一些线性化技术。 课程内容包括： - 如何在花园中安装围栏的优化 - 路径优化问题 - 最大化租车店的收入 - 最优功率流：电力系统 - 其他多个示例，涵盖简单和复杂问题，包括多重约束和求和。 课程采取逐步示范的方式，让学生们一起创建算法。尽管课程侧重于数学方法，您还将学习如何利用人工智能（AI）、遗传算法和粒子群算法来解决问题。无论您是否具备Python编程基础，都无需担心，我将从Python的安装及基础知识讲起，直到复杂的优化问题。我还创建了数学建模的精彩入门，帮助您开始解决实际问题。 希望本课程能对您的职业发展有所帮助。同时，您还将获得Udemy的认证。 运筹学、运筹研究、数学优化，期待在课堂上见到您！
Operational planning and long term planning for companies are more complex in recent years. Information changes fast, and the decision making is a hard task. Therefore, optimization algorithms (operations research) are used to find optimal solutions for these problems. Professionals in this field are one of the most valued in the market.In this course you will learn what is necessary to solve problems applying Mathematical Optimization and Metaheuristics:Linear Programming (LP)Mixed-Integer Linear Programming (MILP)NonLinear Programming (NLP)Mixed-Integer Linear Programming (MINLP)Genetic Algorithm (GA)Multi-Objective Optimization Problems with NSGA-II (an introduction)Particle Swarm (PSO)Constraint Programming (CP)Second-Order Cone Programming (SCOP)NonConvex Quadratic Programming (QP)The following solvers and frameworks will be explored:Solvers: CPLEX - Gurobi - GLPK - CBC - IPOPT - Couenne - SCIP Frameworks: Pyomo - Or-Tools - PuLP - PymooSame Packages and tools: Geneticalgorithm - Pyswarm - Numpy - Pandas - MatplotLib - Spyder - Jupyter NotebookMoreover, you will learn how to apply some linearization techniques when using binary variables.In addition to the classes and exercises, the following problems will be solved step by step:Optimization on how to install a fence in a gardenRoute optimization problemMaximize the revenue in a rental car storeOptimal Power Flow: Electrical SystemsMany other examples, some simple, some complexes, including summations and many constraints.The classes use examples that are created step by step, so we will create the algorithms together.Besides this course is more focused in mathematical approaches, you will also learn how to solve problems using artificial intelligence (AI), genetic algorithm, and particle swarm.Don't worry if you do not know Python or how to code, I will teach you everything you need to start with optimization, from the installation of Python and its basics, to complex optimization problems. Also, I have created a nice introduction on mathematical modeling, so you can start solving your problems.I hope this course can help you in your career. Yet, you will receive a certification from Udemy.Operations Research Operational Research Mathematical Optimization See you in the classes!!
