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MULTIVARIABLE OPTIMIZATION WITH CONSTRAINTS

Format: MS WORD  |  Chapter: 1-5  |  Pages: 75  |  328 Users found this project useful  |  Price NGN3,000

MULTIVARIABLE OPTIMIZATION WITH CONSTRAINTS

ABSTRACT

It has been proved that in non linear programming, there are five methods of solving multivariable optimization with constraints. In this project, the usefulness of some of these methods (Kuhn – Tucker conditions and the Lagrange multipliers) as regards quadratic programming is unveiled. Also, we found out how the other methods are used in solving constrained optimizations and all these are supported with examples to aid better understanding.

Title Page

Approval page

Dedication

Acknowledgement

Abstract

CHAPTER ONE

1.0     Introduction

1.1     Basic definitions

1.2     Layout of work

CHAPTER TWO

2.0        Introduction

2.1     Lagrange Multiplier Method

2.2     Kuhn Tucker Conditions

2.3     Sufficiency of the Kuhn-Tucker Conditions

2.4     Kuhn Tucker Theorems

2.5     Definitions – Maximum and minimum of a function

2.6     Summary

CHAPTER THREE

3.0             Introduction

3.1     Newton Raphson Method

3.2     Penalty Function

3.3     Method of Feasible Directions

3.4     Summary

CHAPTER FOUR

4.0     Introduction

4.3     Methods

4.4     Ways/Procedures of Obtaining the optimal

Solution from the Kuhn-Tucker Conditions

method

4.4.1      The Two-Phase Method

4.4.2      The Elimination Method

4.5     Summary

CHAPTER FIVE

Conclusion

References

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