Linear And Nonlinear Optimization Using Spreadsheets: Examples For Prescriptive, Predictive And Descriptive Analytics
Regular price
€102.99
14 days return policy
Shipping & Delivery
A01=Michael J Brusco
A01=Stephanie Stahl
Age Group_Uncategorized
Age Group_Uncategorized
Author_Michael J Brusco
Author_Stephanie Stahl
automatic-update
Business Analytics
Category1=Non-Fiction
Category=KJT
Category=PBU
Cluster Analysis
COP=Singapore
Delivery_Pre-order
Discriminant Analysis
eq_bestseller
eq_business-finance-law
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Facility Location
Factor Analysis
Integer Programming
Language_English
Linear Programming
Multivariate Statistics
Nonlinear Programming
Optimization
PA=Temporarily unavailable
Portfolio Optimization
Price_€100 and above
Product Design
Production Scheduling
PS=Forthcoming
Regression
Revenue Management
Routing
Scheduling
softlaunch
Sports Analytics
Supply Chain
Workforce Scheduling
Product details
- ISBN 9789811294044
- Publication Date: 01 Nov 2024
- Publisher: World Scientific Publishing Co Pte Ltd
- Publication City/Country: SG
- Product Form: Hardback
- Language: English
Secure
checkout
Fast Shipping
Easy returns
The use of spreadsheets to obtain solutions to a diverse array of examples offers a reader-friendly way of addressing a topic (optimization) that can sometimes be viewed as intimidating. Many people are readily familiar with spreadsheets and how they work, yet are apt to be unaware of the incredible power of Excel for solving some rather complex optimization problems. A major goal of the book is to sell readers on why it is so important to understand optimization, and a large collection of examples for a wide range of business decision making areas (e.g., production planning and scheduling, workforce planning and scheduling, location and supply chain distribution, location of emergency services, assembly line balancing, vehicle routing, project scheduling, revenue management, advertising, product design, payout schedules, productivity measurement, investment portfolio management, sports league scheduling, ranking models, etc.) affords a practical mechanism for achieving that goal. Another important contribution of the book is that it provides coverage of the mechanics of some common yet sophisticated statistical methods (regression, logistic regression, discriminant analysis, factor analysis, and cluster analysis), which are often opaque to many users of such methods.
