Supply Chain Optimization with Mathematical Programming

Introduction

Modern business are exposed to complex supply chains to produce and sell their products.  

To enhance business profitability and customer satisfaction, as well as cater for sustainable operations, competitive advantage can be obtained by businesses that rely on data-driven decision-making tools when designing and managing their supply chains.

In this course, you will learn how to create optimization models to support decision making at the strategic (e.g., location of facilities), tactical (production and inventory planning), and operational (production and transportation) levels when designing and managing supply chains. Additionally, given the importance of coordination across these different levels, you will learn integrated models for coordinated decision making across multiple stages of the supply chain.

In terms of methodology, you will learn about linear, mixed integer and nonlinear programming models, as well as heuristic solution methods to solve some of the decision-making problems encountered in the supply chain context.

Course content

• Overview of supply chain decisions and strategies
• Mathematical modelling via Linear Programming and Integer Linear Programming
• Introduction of some optimization methods (Branch and Bound, simple heuristics) with applications to various supply chain decisions.
• Planning and coordinating demand and supply (Demand forecasting, lot sizing models)
• Inventory management and safety stock analysis
• Transportation planning (Vehicle routing problems)
• Operations scheduling
• Integrated decision making in supply chains