ABSTRACT
Scarce resources must be properly planned and controlled using scientific approaches to control cost of allocating them. The root cause of undue production and high cost of production can neither be easily traced using traditional method nor past experience even computer systems. This study used Linear Programming Model to plan production of Products of Adama Beverages Limited. The aim was to apply Linear Programming Model to determine the products and how many to produce to ascertain Planning and Control of Operational Cost. Secondary Data was collected on supply of products, interview and observation on production process of the company was made, and Linear Programming Model was formulated for the problem. Results were derived using TORA Software. The best products, which will maximize profit, were determined by the model and the company is recommended to embark strictly on scientific approaches to plan production in order to control operational cost.
TABLE OF CONTENT
TITLE PAGE
CERTIFICATION I
DEDICATION II
ACKNOWLEDGMENT III
ABSTRACT IV
TABLE OF CONTENT V
LIST OF TABLES VII
CHAPTER ONE
1.1 BACKGROUND OF STUDY 1
1.2 STATEMENT OF THE PROBLEM 2
1.3 AIM AND OBJECTIVES 3
1.4 JUSTIFICATION OF THE STUDY 3
1.5 SIGNIFICANCE OF THE STUDY 3
1.6 SCOPE OF THE STUDY 3
1.7 DEFINITION OF TERMS: 3
CHAPTER TWO
2.1 INTRODUCTION 5
2.2 LINEAR PROGRAMMING (LP) MODEL 5
2.3 REVIEW OF EMPIRICAL STUDIES ON LP MODEL 6
2.4 THE CONCEPT OF PRODUCTION PLANNING AND CONTROL 7
2.5 THE CONCEPT OF OPERATIONAL COST 10
CHAPTER THREE
3.1 INTRODUCTION 12
3.2 RESEARCH DESIGN 12
3.3 METHOD OF DATA COLLECTION: 12
3.4 METHOD OF DATA ANALYSIS 12
3.5 LINEAR PROGRAMMING MODEL FORMULATION 12
CHAPTER FOUR
4.1 INTRODUCTION 14
4.2 DATA PRESENTATION 14
4.3 ANALYSIS 25
4.4 RESULT OF THE ANALYSIS 26
4.5 DISCUSSION OF THE RESULT 26
CHAPTER FIVE
5.1 SUMMARY: 27
5.2 CONCLUSION: 27
5.5 RECOMMENDATIONS 27
REFERENCES 29
APPENDIX 30
LIST OF TABLES
TABLE 4.1: JANUARY 2015 15
TABLE 4.2: FEBRUARY 2015 15
TABLE 4.3: MARCH 2015 16
TABLE 4.4: APRIL 2015 16
TABLE 4.5: MAY 2015 17
TABLE 4.6: JUNE 2015 17
TABLE 4.7: JULY 2015 18
TABLE 4.8: AUGUST 2015 18
TABLE 4.9: SEPTEMBER 2015 19
TABLE 4.10: OCTOBER 2015 19
TABLE 4.11: NOVEMBER 2015 20
TABLE 4.12: DECEMBER 2015 20
TABLE 4.13: TOTAL MONTHLY DISTRIBUTION IN CARTONS FROM
JANUARY TO JUNE 2015 21
TABLE 4.14: FINISHED GOODS STOCK VALUATION 22
TABLE 4.15: THE BASIC DATA OF THE WHOLE PRODUCTION 23
TABLE 4.16: FINAL ITERATION 25
TABLE 4.17: OPTIMAL SOLUTION 26
