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Introduction

Demand forecasting plays a critical role in supply chain optimization as it helps businesses predict future demand for their products or services. Time series analysis is one of the widely used methods for demand forecasting as it takes into account historical data to make predictions. This thesis aims to explore the application of time series analysis in demand forecasting for supply chain optimization.

1.1 Introduction
1.2 Background of study
1.3 Problem Statement
1.4 Objective of study
1.5 Limitation of study
1.6 Scope of study
1.7 Significance of study
1.8 Structure of the Thesis
1.9 Definition of terms

Chapter Two: Literature Review
2.1 Demand forecasting methods
2.2 Time series analysis
2.3 Supply chain optimization
2.4 Integration of demand forecasting and supply chain optimization
2.5 Benefits of demand forecasting for supply chain optimization
2.6 Challenges in demand forecasting for supply chain optimization
2.7 Case studies on demand forecasting and supply chain optimization
2.8 Technology trends in demand forecasting and supply chain optimization
2.9 Future research directions in demand forecasting and supply chain optimization
2.10 Summary of literature review

Chapter Three: Research Methodology
3.1 Research design
3.2 Data collection methods
3.3 Data analysis techniques
3.4 Selection of time series forecasting models
3.5 Model validation techniques
3.6 Evaluation metrics
3.7 Case study methodology
3.8 Ethical considerations in research
3.9 Limitations of research methodology
3.10 Summary of research methodology

Chapter Four: Discussion of Findings
4.1 Analysis of demand forecasting models
4.2 Impact of demand forecasting on supply chain optimization
4.3 Comparison of different time series forecasting methods
4.4 Case study results
4.5 Implications for practice
4.6 Implications for future research
4.7 Limitations of findings
4.8 Recommendations for businesses
4.9 Conclusions drawn from findings
4.10 Summary of discussion of findings

Chapter Five: Conclusion and Summary
5.1 Summary of key findings
5.2 Implications for businesses
5.3 Contributions to the field of supply chain optimization
5.4 Recommendations for future research
5.5 Conclusion

Thesis Overview

Demand forecasting is vital for businesses to effectively manage their supply chains and optimize operations. Time series analysis is a popular method used in demand forecasting as it leverages historical data to predict future demand patterns. This thesis focuses on exploring the application of time series analysis in demand forecasting for supply chain optimization.

In Chapter One, the introduction provides a background of the study, problem statement, objectives, limitations, scope, significance, and structure of the thesis. Chapter Two will delve into a comprehensive literature review encompassing demand forecasting methods, time series analysis, supply chain optimization, integration of demand forecasting and supply chain optimization, benefits and challenges, case studies, technology trends, and future research directions.

Chapter Three will detail the research methodology including design, data collection, analysis techniques, selection of forecasting models, validation methods, evaluation metrics, case study methodology, ethical considerations, and limitations. Chapter Four will present a discussion of findings through the analysis of demand forecasting models, impact on supply chain optimization, model comparisons, case study results, implications, recommendations, and conclusions. Lastly, Chapter Five will summarize key findings, discuss implications for businesses, contributions to the field, recommendations for further research, and conclude the thesis on demand forecasting for supply chain optimization using time series analysis.

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