Master Linear Programming Methods using Simplex method

Limited resources are a constant challenge for businesses. Whether it's labor, money, materials, or equipment, every resource has a finite quantity, restricting its use. Management's core task is strategically allocating these limited resources to achieve key objectives like profit maximization or cost minimization.

This is where linear programming comes in. A powerful mathematical technique, linear programming helps businesses make optimal decisions about resource allocation. It's applicable across virtually every business function – from production and finance to marketing and distribution – and across all industries.

Linear programming applications are incredibly diverse. Common uses include:

• Production scheduling: Optimizing production plans.
• Assembly line balancing: Improving efficiency in manufacturing.
• Make or buy decisions: Determining whether to produce internally or outsource.
• Media selection: Allocating advertising budgets effectively.
• Profit planning: Forecasting and maximizing profitability.
• Portfolio selection: Optimizing investment strategies.
• Manpower scheduling: Efficiently managing workforce assignments.
• Flight scheduling: Optimizing flight routes and timetables.
• Environment protection: Minimizing environmental impact.
• Diet problems: Creating optimal nutritional plans.

In this course, you'll master the simplex method, a fundamental approach to solving linear programming problems. We will cover various problem types, including:

• Maximization problems: Finding the highest possible value.
• Minimization problems: Finding the lowest possible value.
• Multiple optimal solutions: Dealing with scenarios with several equally good solutions.
• Degeneracy: Understanding and resolving degenerate cases.
• Infeasible solutions: Identifying when a solution is impossible.
• Unrestricted variables: Handling variables with no lower bounds.

You'll also learn the Big M method, a crucial technique for handling constraints expressed as "greater than or equal to" or "equal to" in your linear programming models. This comprehensive understanding will equip you to effectively apply linear programming to real-world business challenges.