• I specialize in teaching Production and Operations Management for engineering and business students. My lessons focus on helping students understand core concepts, solve related problems, and prepare for exams. I stay in contact with students throughout the semester and provide recorded explanatory lectures along with handouts to support learning and revision.
• This course is designed for engineering and management students who want to understand how companies design and manage production systems. We will cover the following key topics:
Introduction to Operations Management
Demand Forecasting
Product and Process Design
Capacity Planning
Facility Location
Facility Layout
Inventory Management
Production Planning and Scheduling
Quality Management
Supply Chain Management
• This course is designed for engineering and management students who want to understand how companies design and manage production systems. We will cover the following key topics:
Introduction to Operations Management
Demand Forecasting
Product and Process Design
Capacity Planning
Facility Location
Facility Layout
Inventory Management
Production Planning and Scheduling
Quality Management
Supply Chain Management
A comprehensive course in Linear Programming and Linear Optimization, based on the renowned reference:
Bertsimas, D., & Tsitsiklis, J. N. (1997). Introduction to Linear Optimization. Athena Scientific.
The course covers the first five chapters in their entirety, forming the foundation upon which everything that follows in mathematical improvement is built. The concepts are explained in clear Arabic with step-by-step solved examples, illustrations, and practice exercises.
The five lectures:
Lecture 1 — Introduction to Linear Optimization:
What is optimization? And why do we need it?
Variables, decisions, functions, and constraints
The general formula for linear programming
Standard Form
Reducing any issue to the standard formula
Piecewise Linear Convex Functions
Graphing and solution
Fundamentals of Linear Algebra
Analysis of algorithms and number of operations
Lecture 2 — Linear Programming Basics (LP Basics):
Practical examples: food issues, production, scheduling, networks, pattern classification
Converting problems to standard format
Remove free variables
Slack and Surplus variables
convex and concave functions
Absolute values in objective functions
Graphical solution in 2D and 3D
The five possible solutions
Lecture 3 — Geometry of Linear Programming (LP):
Polyhedron and Polytope
Hyperplanes & Halfspaces
Extreme Points
Vertices
Basic Feasible Solutions
Active Constraints
Degeneration
The presence of extreme points
Visual examples in 2D and 3D
Lecture 4 — The Simplex Method:
Optimality Conditions
Reduced Costs
Development of the Simplex algorithm
Simplex Tableau
Pivoting
The Revised Simplex Method
Cycling and how to avoid it
Bland's Rule
Finding a basic, possible, initial solution
Two-Phase Simplex Method
Big-M Method
Mathematical aptitude and average behavior
Klee-Minty cube
Lecture 5 — Duality Theory:
The original (Primal) and dual problem
The relationship between variables and constraints
Weak Duality Theory
Strong Duality Theory
Conditions for Complementary Slackness
Dual variables as marginal costs
Shadow Prices
Dual Simplex Method
Geometric interpretation of duality
Applications in Economics and Finance
Advantages:
🎯 Explanation based on an accredited academic reference
📐 Illustrations for each geometric concept
🧮 Solved examples with numbers
💻 Examples in Python using gurobipy
📊 Comparison tables between different formulas
🔗 Linking theory to practical applications
📝 Exercises at the end of each lecture
Bertsimas, D., & Tsitsiklis, J. N. (1997). Introduction to Linear Optimization. Athena Scientific.
The course covers the first five chapters in their entirety, forming the foundation upon which everything that follows in mathematical improvement is built. The concepts are explained in clear Arabic with step-by-step solved examples, illustrations, and practice exercises.
The five lectures:
Lecture 1 — Introduction to Linear Optimization:
What is optimization? And why do we need it?
Variables, decisions, functions, and constraints
The general formula for linear programming
Standard Form
Reducing any issue to the standard formula
Piecewise Linear Convex Functions
Graphing and solution
Fundamentals of Linear Algebra
Analysis of algorithms and number of operations
Lecture 2 — Linear Programming Basics (LP Basics):
Practical examples: food issues, production, scheduling, networks, pattern classification
Converting problems to standard format
Remove free variables
Slack and Surplus variables
convex and concave functions
Absolute values in objective functions
Graphical solution in 2D and 3D
The five possible solutions
Lecture 3 — Geometry of Linear Programming (LP):
Polyhedron and Polytope
Hyperplanes & Halfspaces
Extreme Points
Vertices
Basic Feasible Solutions
Active Constraints
Degeneration
The presence of extreme points
Visual examples in 2D and 3D
Lecture 4 — The Simplex Method:
Optimality Conditions
Reduced Costs
Development of the Simplex algorithm
Simplex Tableau
Pivoting
The Revised Simplex Method
Cycling and how to avoid it
Bland's Rule
Finding a basic, possible, initial solution
Two-Phase Simplex Method
Big-M Method
Mathematical aptitude and average behavior
Klee-Minty cube
Lecture 5 — Duality Theory:
The original (Primal) and dual problem
The relationship between variables and constraints
Weak Duality Theory
Strong Duality Theory
Conditions for Complementary Slackness
Dual variables as marginal costs
Shadow Prices
Dual Simplex Method
Geometric interpretation of duality
Applications in Economics and Finance
Advantages:
🎯 Explanation based on an accredited academic reference
📐 Illustrations for each geometric concept
🧮 Solved examples with numbers
💻 Examples in Python using gurobipy
📊 Comparison tables between different formulas
🔗 Linking theory to practical applications
📝 Exercises at the end of each lecture
I specialize in teaching Operations Research 1 for engineering and management students. My lessons focus on helping students understand core concepts, solve related problems, and prepare for exams. I stay in contact with students throughout the semester and provide recorded explanatory lectures along with handouts to support learning and revision.
This course is designed for engineering and management students who want to learn how to apply mathematical and analytical techniques to make better decisions in production, operations, and business systems.
We will cover key topics such as:
Introduction to Operations Research
Linear Programming
Simplex Method
Transportation and Assignment Problems
Integer Programming
Network Models (Shortest Path, Max Flow, Min Cost Flow)
Project Management Techniques (PERT/CPM)
Students will learn how to formulate real-world problems mathematically, analyze them using OR techniques, and interpret the results to make effective operational decisions.
This course is designed for engineering and management students who want to learn how to apply mathematical and analytical techniques to make better decisions in production, operations, and business systems.
We will cover key topics such as:
Introduction to Operations Research
Linear Programming
Simplex Method
Transportation and Assignment Problems
Integer Programming
Network Models (Shortest Path, Max Flow, Min Cost Flow)
Project Management Techniques (PERT/CPM)
Students will learn how to formulate real-world problems mathematically, analyze them using OR techniques, and interpret the results to make effective operational decisions.
I am Engineer Abdel Rahman Abdel Aal, a university instructor specializing in explaining engineering subjects in a simplified and interactive manner via Zoom.
God willing, our lessons aim to provide a deep and systematic understanding of the curriculum content, through simplified and interactive explanations that adapt to each student's level.
🔹 Short tests are given periodically to measure understanding and stimulate concentration, while clarifying the differences between similar concepts to prevent distraction.
🔹 I rely on various examples, patience, and gradual delivery of information in my explanation, until the student reaches full understanding with confidence.
🔹 There is continuous follow-up via WhatsApp or Telegram throughout the semester to answer questions and help the student with studying and solving problems as they occur.
💻 The explanation is conducted online via Zoom, with a full recording of each session provided, so that the student can review it at any time.
🎯 Our goal is not just to pass the subject, but to excel in it and understand it in an easy and consistent manner, God willing.
God willing, our lessons aim to provide a deep and systematic understanding of the curriculum content, through simplified and interactive explanations that adapt to each student's level.
🔹 Short tests are given periodically to measure understanding and stimulate concentration, while clarifying the differences between similar concepts to prevent distraction.
🔹 I rely on various examples, patience, and gradual delivery of information in my explanation, until the student reaches full understanding with confidence.
🔹 There is continuous follow-up via WhatsApp or Telegram throughout the semester to answer questions and help the student with studying and solving problems as they occur.
💻 The explanation is conducted online via Zoom, with a full recording of each session provided, so that the student can review it at any time.
🎯 Our goal is not just to pass the subject, but to excel in it and understand it in an easy and consistent manner, God willing.
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