运筹学:一种积极的方法

Operations Research: an Active Approach

Learn the methodology and some prominent techniques of Operations Research to make informed decisions for solving your operational problems without the need of advanced mathematics.

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香港理工大学
edX
  • 完成时间大约为 6
  • 中级
  • 英语
注:因开课平台的各种因素变化,以上开课日期仅供参考

你将学到什么

understand and apply the methodology of Operations Research to investigate and tackle your operational problems;

formulate and apply the techniques of Linear Programming and the extended topics to solve certain optimization problems;

apply the techniques of Critical Path Method and PERT in project management;

appreciate the use of simulation in studying the behaviour of stochastic operations systems;

and understand the limitations of these techniques.

课程概况

Operations management deals with operational planning and control issues, and is needed in all sectors of the society. One of the challenges to operations manager is how to make use of the available resources in the best way for meeting a certain objective. Quantitative approaches are inevitably needed in tackling many of such problems.

Operations Research (OR) deals with problem formulation and application of analytical methods to assist in decision-making of operational problems in planning and control. The techniques of OR are useful quantitative tools to assist operations managers, and has a wide applicability in engineering, manufacturing, construction, financial and various service sectors.

Operations Research is an applied mathematics subject and is also a course in many engineering and management programmes. This course is designed for both students learning OR and learners who are practitioners in their respective professionals. The mathematical procedures for the OR techniques are introduced in details in the examples provided in the course. This helps learners to master the methodology and the techniques and apply them to achieve their goals through active learning.

This course introduces two prominent OR techniques and their extended topics. The Simplex Method for Linear Programming (LP) has been considered one of the top 10 algorithms of the 20th century. LP is an optimization technique for solving problems such as finding the optimal product mix, production plan, and shipment allocation, in order to maximize the profir or minimize the cost. The Critical Path Method (CPM) is a popular technique employed by project managers in scheduling project activities. Some extended topics of CPM are also introduced to deal with certain special situations in project management.

In reality, many systems operate under stochastic environment and the operational problems cannot be solved by the known analytical methods. To this end, the simulation approach is introduced in the last chapter of this course. Simulation is a powerful technique for tackling OR problems under such situations.

课程大纲

Chapter 0: Introduction to Operations Research

Chapter 1: Linear Programming and Simplex Method

Introduction to of linear programming (LP) problem, formulating a problem as an LP problem, simplex method in solving maximization and minimization LP problems

Chapter 2: Further Techniques in Simplex Method

Artificial variables in simplex method, M-method, two-phase method, sensitivity analysis, special cases in simplex

Chapter 3: Transportation Problem and Assignment Problem

Introduction and modelling of transportation problem, transportation algorithm, introduction to assignment model, solving assignment problems by the Hungarian method

Chapter 4: Critical Path Method for Project Scheduling

Introduction to project management and network models, network representations for projects, determination of project duration by the critical path method (CPM), using a time schedule in assisting project planning and control

Chapter 5: Further Topics in Critical Path Method

Project crashing, Program evaluation and review techniques (PERT)

Chapter 6: Simulation

Introduction to simulation, generation of random variates, examples of applications of simulation

预备知识

Knowledge of mathematics at high school level
Knowledge of probability distributions and statistics, and preferably basic calculus, for learning Simulation

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