Introduction to Management Science Hillier pdf下载

"Introduction to Management Science, 4e", offers a unique model approach and integrates the use of Excel. Through this approach students are better able to grasp the essential concepts covered in the course and see their utility. Each chapter includes a case study that is meant to show the students a real and interesting application of the topics addressed in that chapter. These cases and related applications cut across all functional areas of business and show how management science techniques apply in the business environment.

Summary:
The future success of any business depends heavily on the ability of its management to forecast well. Forecasting may be needed in several areas, including sales, the need for spare parts, production yields, economic trends, and staff needs.
A time series is a series of observations over time of some quantity of interest. Several statistical forecasting methods use these observations in some way to forecasting what the next value will be. These methods include the last-value method, the averaging method, the moving-average method, the exponential smoothing method, and exponential smoothing with trend.
The goal of all these methods is to estimate the mean of the underlying probability distribution of the next value of the time series as closely as possible. This may require using seasonal factors to seasonally adjust the time series, as well as identifying other factors that may cause this underlying probability distribution to shift from one time period to the next.
Another statistical forecasting approach is called causal forecasting. This approach obtains a forecast of the quantity of interest (the dependent variable) by relating it directly to one or more other quantities (the independent variables) that drive the quantity of interest. Frequently, this involves using linear regression to approximate the relationship between the dependent variable and each independent variable by a straight line.
The software accompanying this book includes Excel templates for the various statistical forecasting methods, a forecasting module in the Interactive Management Science Modules, and a commercial Excel add-in called CB Predictor for performing time-series forecasting within a spreadsheet environment.
Still another key category of forecasting methods is judgmental methods. This category involves basing the forecast on a manager's opinion, a jury of executive opinion, a sales force composite, a consumer market survey, or the Delphi method.