ForecastIT 3. Simple Exponential Smoothing
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This document provides an overview of simple exponential smoothing, a technique for forecasting future values based on past observations. It describes the basic smoothing equation used in the method and notes that simple exponential smoothing is best for data without trends or seasonality. The document then outlines the steps for applying simple exponential smoothing, including setting objectives, building a model using software, evaluating the model's accuracy, and using the model to generate forecasts. An example using mortgage rate data demonstrates how to implement the method.
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Demand forecasting is essential for businesses to plan production levels. Common demand forecasting techniques include surveys of consumer intentions, expert opinions, analysis of historical sales data, and use of economic indicators related to demand. The optimal approach considers multiple techniques and applies judgment to account for uncertain factors. Forecasts should be presented to management simply with key assumptions and margin of error highlighted.
Plant Location
Plant location involves choosing an ideal region and site for a business or factory. An ideal location minimizes costs while maximizing market share, profits, and social benefits. Location studies consider regional, community, and site-specific factors. Key factors in choosing a location include: availability of raw materials, proximity to markets, transportation access, labor supply, infrastructure like power and capital, natural resources, government incentives, and personal preferences. Locations may be urban, rural, or suburban areas, each with their own advantages and disadvantages regarding costs, space, resources, and regulations. Models for evaluating potential locations include factor rating, point rating, and qualitative factor analysis. Governments influence location decisions to promote balanced regional development.
Plant location
The document discusses the steps involved in selecting a location for a new industrial plant. The key steps are: 1) Deciding whether to locate domestically or internationally; 2) Selecting a suitable region based on factors like raw materials, markets, infrastructure, climate, and government policies; 3) Choosing a specific community or locality based on availability of labor, financing options, and amenities for workers; 4) Picking the exact site based on soil quality, size, topography, and waste disposal needs. Location is a critical economic decision that impacts long-term costs and business operations.
Time Series
Time series analysis involves analyzing data collected over time. A time series is a set of data points indexed in time order. The key components of a time series are trends, seasonality, cycles, and irregular variations. Trend refers to the long-term movement of a time series over time. Seasonality refers to periodic fluctuations that occur each year, such as higher sales in winter. Cyclical variations are longer term fluctuations in business cycles. Irregular variations are random, unpredictable fluctuations. Time series analysis is important for forecasting, economic analysis, and business planning. Common methods for analyzing time series components include moving averages, least squares regression, decomposition models, and harmonic analysis.
Amazon.com Supply chain management- case study
Amazon operates a large global supply chain network to support its e-commerce business. It has around 50 warehouses globally, including 20 in the US, to store and fulfill customer orders. Amazon uses a mix of in-house inventory and third-party suppliers to stock products. It aims to deliver most items within one day of ordering to stay competitive. Amazon's supply chain is designed for cost-effectiveness and responsiveness to meet high customer service levels and the wide range of customer demand.
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The document describes Winter's Method for seasonal time series forecasting. It involves three steps:
1) Decomposing the time series into seasonal, trend, and error components.
2) Using exponential smoothing to update estimates of the deseasonalized series, seasonal factors, and trend over time.
3) Forecasting by combining the updated seasonal, trend, and error estimates. The initialization procedure calculates initial values for the trend, seasonal factors, and series based on historical data.
time series analysis
This document provides an overview of time series analysis and its key components. It discusses that a time series is a set of data measured at successive times joined together by time order. The main components of a time series are trends, seasonal variations, cyclical variations, and irregular variations. Time series analysis is important for business forecasting, understanding past behavior, and facilitating comparison. There are two main mathematical models used - the additive model which assumes data is the sum of its components, and the multiplicative model which assumes data is the product of its components. Decomposition of a time series involves discovering, measuring, and isolating these different components.
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CHAPTER Modeling and Analysis Heuristic Search Methods .docx
CHAPTER
Modeling and Analysis: Heuristic
Search Methods and Simulation
LEARNING OBJECTIVES
• Explain the basic concepts of simulation
and heuristics, and when to use them
• Understand how search methods are
used to solve some decision support
models
• Know the concepts behind and
applications of genetic algorithms
• Explain the differences among
algorithms, blind search, and heuristics
• Understand the concepts and
applications of different types of
simulation
• Explain what is meant by system
dynamics, agent-based modeling, Monte
Carlo, and discrete event simulation
• Describe the key issues of model
management
I n this chapter, we continue to explore some additional concepts related to the model base, one of the major components of decision support systems (DSS). As pointed out in the last chapter, we present this material with a note of caution: The purpose
of this chapter is not necessarily for you to master the topics of modeling and analysis.
Rather, the material is geared toward gaining familiarity with the important concepts
as they relate to DSS and their use in decision making. We discuss the structure and
application of some successful time-proven models and methodologies: search methods,
heuristic programming, and simulation. Genetic algorithms mimic the natural process of
evolution to help find solutions to complex problems. The concepts and motivating appli-
cations of these advanced techniques are described in this chapter, which is organized
into the following sections:
10.1 Opening Vignette: System Dynamics Allows Fluor Corporation to Better Plan
for Project and Change Management 436
10.2 Problem-Solving Search Methods 437
10.3 Genetic Algorithms and Developing GA Applications 441
10.4 Simulation 446
435
436 Pan IV • Prescriptive Analytics
10.5 Visu al Interactive Simulatio n 453
10.6 System Dynamics Modeling 458
10.7 Agents-Based Mode ling 461
10.1 OPENING VIGNETTE: System Dynamics Allows Fluor
Corporation to Better Plan for Project and Change
Management
INTRODUCTION
Fluor is an engineering and construction company with over 36,000 employers spread
over several countries worldwide . The company's net income in 2009 amounted to
about $680 million based on total revenue o f $22 b illion. As part of its operations, Fluor
manages varying sizes of projects that are subject to scope changes, design changes, and
schedule changes.
PRESENTATION OF PROBLEM
Fluor estimated that changes accounted for about 20 to 30 percent of revenue . Most
changes were due to secondary impacts like ripple effects, disruptions, and p roductivity
loss. Previously, the changes were collated and reported at a later period and the burden
of cost allocated to the stakeholder responsible. In certain instances when late su rprises
abou t cost and project schedule are attributed to clients, it causes friction between
clients and Fluor, w hich eventually affect future business dealings. .
CHAPTER Modeling and Analysis Heuristic Search Methods .docx
CHAPTER
Modeling and Analysis: Heuristic
Search Methods and Simulation
LEARNING OBJECTIVES
• Explain the basic concepts of simulation
and heuristics, and when to use them
• Understand how search methods are
used to solve some decision support
models
• Know the concepts behind and
applications of genetic algorithms
• Explain the differences among
algorithms, blind search, and heuristics
• Understand the concepts and
applications of different types of
simulation
• Explain what is meant by system
dynamics, agent-based modeling, Monte
Carlo, and discrete event simulation
• Describe the key issues of model
management
I n this chapter, we continue to explore some additional concepts related to the model base, one of the major components of decision support systems (DSS). As pointed out in the last chapter, we present this material with a note of caution: The purpose
of this chapter is not necessarily for you to master the topics of modeling and analysis.
Rather, the material is geared toward gaining familiarity with the important concepts
as they relate to DSS and their use in decision making. We discuss the structure and
application of some successful time-proven models and methodologies: search methods,
heuristic programming, and simulation. Genetic algorithms mimic the natural process of
evolution to help find solutions to complex problems. The concepts and motivating appli-
cations of these advanced techniques are described in this chapter, which is organized
into the following sections:
10.1 Opening Vignette: System Dynamics Allows Fluor Corporation to Better Plan
for Project and Change Management 436
10.2 Problem-Solving Search Methods 437
10.3 Genetic Algorithms and Developing GA Applications 441
10.4 Simulation 446
435
436 Pan IV • Prescriptive Analytics
10.5 Visu al Interactive Simulatio n 453
10.6 System Dynamics Modeling 458
10.7 Agents-Based Mode ling 461
10.1 OPENING VIGNETTE: System Dynamics Allows Fluor
Corporation to Better Plan for Project and Change
Management
INTRODUCTION
Fluor is an engineering and construction company with over 36,000 employers spread
over several countries worldwide . The company's net income in 2009 amounted to
about $680 million based on total revenue o f $22 b illion. As part of its operations, Fluor
manages varying sizes of projects that are subject to scope changes, design changes, and
schedule changes.
PRESENTATION OF PROBLEM
Fluor estimated that changes accounted for about 20 to 30 percent of revenue . Most
changes were due to secondary impacts like ripple effects, disruptions, and p roductivity
loss. Previously, the changes were collated and reported at a later period and the burden
of cost allocated to the stakeholder responsible. In certain instances when late su rprises
abou t cost and project schedule are attributed to clients, it causes friction between
clients and Fluor, w hich eventually affect future business dealings. ...
Similar to ForecastIT 3. Simple Exponential Smoothing (20)
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CHAPTER Modeling and Analysis Heuristic Search Methods .docx
CHAPTER Modeling and Analysis Heuristic Search Methods .docx
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May’s reports showed signs of continued economic growth, said Sam Millette, director, fixed income, in his latest Economic Risk Factor Update.
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你做代理，可以改变自己，改变他人，给他人和自己一个机会美景更增添一份性感夹杂着一份纯洁的妖娆毫无违和感实在给人带来一份悠然幸福的心情如果说现在的审美已经断然拒绝了无声的话那么在树林间飞掠而过的小鸟叽叽咋咋的叫声是否就是这最后的点睛之笔悠然走在林间的小路上宁静与清香一丝丝的盛夏气息吸入身体昔日生活里的繁忙与焦躁早已淡然无存心中满是悠然清淡的芳菲身体不由的轻松脚步也感到无比的轻快走出这盘栾交错的小道眼前是连绵不绝的山峦浩荡天地间大自然毫无吝啬的展现它的达
Independent Study - College of Wooster Research (2023-2024) FDI, Culture, Glo...
Independent Study - College of Wooster Research (2023-2024) FDI, Culture, Glo...AntoniaOwensDetwiler
"Does Foreign Direct Investment Negatively Affect Preservation of Culture in the Global South? Case Studies in Thailand and Cambodia."
Do elements of globalization, such as Foreign Direct Investment (FDI), negatively affect the ability of countries in the Global South to preserve their culture? This research aims to answer this question by employing a cross-sectional comparative case study analysis utilizing methods of difference. Thailand and Cambodia are compared as they are in the same region and have a similar culture. The metric of difference between Thailand and Cambodia is their ability to preserve their culture. This ability is operationalized by their respective attitudes towards FDI; Thailand imposes stringent regulations and limitations on FDI while Cambodia does not hesitate to accept most FDI and imposes fewer limitations. The evidence from this study suggests that FDI from globally influential countries with high gross domestic products (GDPs) (e.g. China, U.S.) challenges the ability of countries with lower GDPs (e.g. Cambodia) to protect their culture. Furthermore, the ability, or lack thereof, of the receiving countries to protect their culture is amplified by the existence and implementation of restrictive FDI policies imposed by their governments.
My study abroad in Bali, Indonesia, inspired this research topic as I noticed how globalization is changing the culture of its people. I learned their language and way of life which helped me understand the beauty and importance of cultural preservation. I believe we could all benefit from learning new perspectives as they could help us ideate solutions to contemporary issues and empathize with others.一比一原版(UCSB毕业证)圣芭芭拉分校毕业证如何办理
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【主营项目】
一.圣芭芭拉分校毕业证成绩单使馆认证教育部认证成绩单等！
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四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
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招聘代理：本公司诚聘英国加拿大澳洲新西兰美国法国德国新加坡各地代理人员如果你有业余时间有兴趣就请联系我们咨询顾问：+微信:95270640田里逡巡一番抱起一只硕大的西瓜用石刀劈开抑或用拳头砸开每人抱起一大块就啃啃得满嘴满脸猴屁股般的红艳大家一个劲地指着对方吃吃地笑瓜裂得古怪奇形怪状却丝毫不影响瓜味甜丝丝的满嘴生津遍地都是瓜横七竖八的活像掷满了一地的大石块摘走二三只爷爷是断然发现不了的即便发现爷爷也不恼反而教山娃辨认孰熟孰嫩孰甜孰淡名义上是护瓜往往在瓜棚里坐上一刻饱吃一顿后山娃就领着阿黑漫山遍野地跑阿黑是一条黑色的大猎狗挺机灵的是山室
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"Does Foreign Direct Investment Negatively Affect Preservation of Culture in the Global South? Case Studies in Thailand and Cambodia."
Do elements of globalization, such as Foreign Direct Investment (FDI), negatively affect the ability of countries in the Global South to preserve their culture? This research aims to answer this question by employing a cross-sectional comparative case study analysis utilizing methods of difference. Thailand and Cambodia are compared as they are in the same region and have a similar culture. The metric of difference between Thailand and Cambodia is their ability to preserve their culture. This ability is operationalized by their respective attitudes towards FDI; Thailand imposes stringent regulations and limitations on FDI while Cambodia does not hesitate to accept most FDI and imposes fewer limitations. The evidence from this study suggests that FDI from globally influential countries with high gross domestic products (GDPs) (e.g. China, U.S.) challenges the ability of countries with lower GDPs (e.g. Cambodia) to protect their culture. Furthermore, the ability, or lack thereof, of the receiving countries to protect their culture is amplified by the existence and implementation of restrictive FDI policies imposed by their governments.
My study abroad in Bali, Indonesia, inspired this research topic as I noticed how globalization is changing the culture of its people. I learned their language and way of life which helped me understand the beauty and importance of cultural preservation. I believe we could all benefit from learning new perspectives as they could help us ideate solutions to contemporary issues and empathize with others.
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ForecastIT 3. Simple Exponential Smoothing
- 1. Simple Exponential Smoothing Lesson #3 Simple Exponential Smoothing Method Copyright 2010 DeepThought, Inc. 1
- 3. Estimates a smoothing equation
- 4. Uses the estimated smoothing equation to forecast future values
- 6. F(t+1) = a × X(t) + (1-a) × F(t)Copyright 2010 DeepThought, Inc. 2
- 8. Fits a smoothing equation to data
- 9. Estimating a smoothing equation which minimizes the errors between actual data points and model estimates
- 10. When to use method
- 11. Data has no trend or seasonality
- 13. When not to use
- 14. Data exhibits pattern such as trend, seasonality, cyclicalityCopyright 2010 DeepThought, Inc. 3
- 15. Simple Exponential Smoothing Forecasting Steps Set an objective Build model Evaluate model Use model Copyright 2010 DeepThought, Inc. 4
- 17. Simple exponential smoothing allows to test whether a smoothing technique works as a model. Objectives should take that principal under consideration
- 18. Example objectives for 30-Year Conventional Mortgage Rate (see next slide):
- 19. Test if 30 Yr. Mortgage Rate can be fit to a simple exponential smoothing model
- 20. If 30 Yr. Mortgage Rate exhibits a statistically significant fit, review and interpret results
- 21. If model looks good, create a forecast based off modelCopyright 2010 DeepThought, Inc. 5
- 22. Simple Exponential Smoothing Example: 30-Year Conventional Mortgage Rate Copyright 2010 DeepThought, Inc. 6
- 23. Simple Exponential Smoothing Adjust Time Frame Copyright 2010 DeepThought, Inc. 7
- 26. Mean
- 27. Variance & Standard Deviation
- 28. Accuracy / Error
- 29. SSE
- 30. RMSE
- 31. MAPE
- 32. R2; Adjusted R2
- 34. F-Test
- 35. P-Value F-TestCopyright 2010 DeepThought, Inc. 9
- 37. 5.88
- 38. Variance
- 39. 0.34
- 41. 0.58Copyright 2010 DeepThought, Inc. 10
- 43. 1.97
- 44. RMSE
- 45. 0.22
- 46. MAPE
- 47. 2.78%
- 48. R2; Adjusted R2
- 49. 84.80%
- 50. 84.39%Copyright 2010 DeepThought, Inc. 11
- 52. 55.80
- 53. P-Value F-Test
- 54. 0.000021Copyright 2010 DeepThought, Inc. 12
- 56. Will use accuracy/error statistics to compare multiple models to find best modelsCopyright 2010 DeepThought, Inc. 13
- 58. Answer objectivesCopyright 2010 DeepThought, Inc. 14
- 60. 4.888234437Copyright 2010 DeepThought, Inc. 15