Linear and Nonlinear Optimization using Spreadsheets:Examples for Prescriptive, Predictive and Descriptive Analytics

Michael J Brusco and Stephanie Stahl
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Michael J Brusco: Florida State University, USA

in World Scientific Books from World Scientific Publishing Co. Pte. Ltd.

Abstract: 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.

Keywords: Optimization; Business Analytics; Linear Programming; Integer Programming; Nonlinear Programming; Multivariate Statistics; Regression; Cluster Analysis; Factor Analysis; Discriminant Analysis; Supply Chain; Facility Location; Routing; Scheduling; Workforce Scheduling; Production Scheduling; Revenue Management; Product Design; Portfolio Optimization; Sports Analytics (search for similar items in EconPapers)
JEL-codes: C44 C61 M11 (search for similar items in EconPapers)
Date: 2024
ISBN: 9789811294044
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