**Lesson One: Matrix Algebra**

1.0 Lesson Objectives

1.1 Introduction

1.2 Types of Matrices

1.3 Matrix Operations

1.4 Application of Matrix Algebra

1.4.1 Modeling Solving Simultaneous Equations

1.5.2 Input-Output Analysis

1.5.2.1. Introduction

1.5.2.2 Types of Input-Output Models

1.5.2.3 Derivation of Input-Output Modes

1.5.3 Markov Analysis

1.5.3.1 Introduction

1.5.3.2 Assumption of Markov Analysis and Markove Process Inputs

1.5.3.3. Transition Probabilities

1.5.3.4 Initial Conditions

1.5.3.5 Steady State (Equilibrium) Condition

Exercise One: Matrix Algebra and its Applications

**Lesson Two: Linear Programming**

2.0 Objectives

2.1 Introduction

2.2 Requirements for Linear Programming Models

2.3 Linear Programming Problems Classification

2.4 General Applications of Linear Programming

2.5 Formulation of Linear Programming Models

2.5.1 Maximization Problems

2.5.2 Minimization Problems

2.6 Linear Programming Solution Techniques

2.6.1 Graphical Method

2.6.1.1. Maximization Problem Solution

2.6.1.2 Minimization Problem Solution

2.6.2 Simplex Algorithm (Procedure)

2.6.2.1 Basic Concept

2.6.2.2. The Simplex Procedure

2.6.2.3 Procedure for Maximization Problem

2.6.2.4 Procedure for Minimization Problem

Exercise Two: Linear Programming

**Lesson Three: Probability Theory 64**

3.0 Objectives

3.1 Introduction

3.2 Basic concepts

3.2.1 Random Experience

3.3. Types Of Events

3.3.1 Mutually Exclusive And Exhaustive Events

3.3.2 Mutually Exclusive and Exhaustive Events

3.3.3. Compound Events

3.3.4 Impossible Events

3.3.5. Complementary Events

3.4 Laws of Probability of Events

3.4 Techniques Of Counting

3.4.1 Tree Diagram

3.4.3 Permutation

3.4.4 Combination

Exercise 2: Probability Theory

**Lesson Four: Decision Theory **

4.0 Objectives

4.1 Introduction

4.2 Structure of Decision Analysis

4.3 Types of Decisions

4.3.1 Deterministic Decision Making Criteria

4.3.2 Expected Monetary Value (EMV) Criterion

4.4. Decision Tree Approach

4.4.1 Construction of Decision Trees.

**Lesson Five: Inventory Control**

5.0 Objectives

5.1. Introduction

5.2 Inventory Level Objectives

5.3 Factors Characterizing Inventory Systems

5.4 Inventory Control Policies

5.4.1 Fixed Order Quantity Policy

5.5 Inventory Control Costs

5.5.1 Basic Inventory Control Model: Economic Order Quantity (EOQ) Model

5.5.2 Derivation of Model

5..6 Stochastic Demand

5.6.1 Safety Stock Determination

# Buy Full Notes @ KES 100 soft copy

## One thought on “BMS 102: Management Mathematics II Notes”