Supply Chain Analytics (Coursera)

In this course, we will discuss key concepts and decision problems such as transportation problems, travelling salesman, assignment, job shop scheduling, inventory, forecasting and production planning. In solving these problems, we make use of linear and integer programming and some other heuristics. With continued practice you will become better at these skills. We will cover a couple of case studies on electricity markets and supplier selection in detail. This course will prepare you to explore the other related advancements in this area.

Syllabus

Linear Programming and Transportation Problem
Linear programming is a mathematical optimisation technique used to find the maximum or minimum value of a linear objective function subject to a set of linear constraints. Linear programming can be used to solve a variety of optimisation problems, such as finding the most cost-effective way to produce a product or allocate resources. Google OR-Tools is a software suite that includes various tools for solving optimisation problems, including linear programming problems. OR-Tools is available for free and can be used with a variety of programming languages. In this module, we use Google OR-Tools using Python. It is widely used in various industries and applications, such as logistics, supply chains, and operations management. The transportation problem is a specific type of linear programming problem that involves finding the most cost-effective way to transport goods from a set of origins to a set of destinations. The goal is to minimise the total transportation cost while meeting the demand at each destination. In this module, we also explain Google OR-Tools for solving transportation problems.

Inventory Management
Inventory is a practice for managing supply chains. It has its benefits as well as costs. In this module, you will learn about inventory and how it contrasts with other prevalent ideas in managing supply chains. You will also learn how they tend to gain prominence basis the wider context. You will be able to build simple models to understand the decision-making related to inventory and gradually introduce realism into the basic models.

Integer Programming
Integer programming is a type of mathematical optimisation technique. It is used to find the maximum or minimum value of a linear objective function, subject to a set of linear constraints, where some or all of the variables are restricted to be integers. This type of optimisation is useful in situations where the variables must be integers, such as when representing the number of items to be produced or the number of resources to be allocated. The supplier selection problem is a specific type of integer programming problem that involves selecting the best suppliers for a given set of products or services. The goal is to minimise the total cost of purchasing goods or services from the suppliers while meeting the demand at each destination. The supplier selection problem can be solved using a variety of algorithms and methods, such as branch-and-bound and cutting-plane algorithms. In this module, you will learn the applications of Google OR-Tools for integer programming and supplier selection problems.

Reinforcement Learning
In this module, you will learn about the Multi-Armed Bandit problem. The module will help you to apply the algorithms for the Multi-Armed Bandit problem.

Case Study on Supplier Selection
You will learn the concept of supplier selection with the help of a case study. The scenario details you to consider a multinational corporation with several departments across countries. The company is looking to standardize its supply chain operations and improve its overall efficiency. To achieve this, it has decided to select suppliers for the goods it requires. The supplier selection problem aims to choose the best supplier based on various criteria such as cost, quality, delivery time, and reliability. At the same time, the company would like to minimise the risk. You will learn to predict a supplier’s risk using the supervised learning (classification) paradigm. Furthermore, you will be able to incorporate this in an optimisation problem to make an efficient supplier selection. 

Forecasting
Anticipating consumer demand is necessary to meet the demand in a reasonable time frame. The processes involved in making a product and delivering it to the customer would usually require time that exceeds the time the consumer is willing to wait. This is where forecasting has a crucial role to play in planning and decision-making. The uncertainty surrounding the future is both exciting and challenging, with businesses seeking to maximise the positives and minimise the risks. This module provides an overview of the key terms and ideas underlying the prevalent techniques used in forecasting.

Production Planning
In this module, you will learn about production planning and various aspects of it. Organisations have to make varied decisions from time to time. Production planning constitutes an important set of decisions taken at an intermediate time horizon, e.g., every few months. These decisions are tactical and constitute variables such as inventory, hiring, firing, overtime, and subcontracting. Systemic variables, such as facility location and capacity, are the bounds within which production planning operates.

Case study of Electricity Spot Markets
In this module, you will learn about a case study that discusses the electricity sector in the application of the optimisation paradigm. You will also learn about the concepts of market structure, supply and demand curves, consumers, producer surplus, and social welfare maximisation. The spot markets are a channel for procurement. You will learn how the spot markets discover prices and delve into bidding strategies for consumers and producers.

Decision Making in SCM
In this module, you will get an understanding of the key concepts and techniques used in supply chain management, with a focus on assignment problems, traveling salesman problems, and job-shop scheduling problems. You will be introduced to the mathematical programming formulation of these problems. You will also learn to use tools and software to design and implement solutions to complex supply chain challenges and will gain practical skills in the areas of decision-making models. This module is applicable to a wide range of industries and organisations.