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Business Analytics for Decision Making (Hardcover)
Loot Price: R2,971
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Business Analytics for Decision Making (Hardcover)
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Business Analytics for Decision Making, the first complete text
suitable for use in introductory Business Analytics courses,
establishes a national syllabus for an emerging first course at an
MBA or upper undergraduate level. This timely text is mainly about
model analytics, particularly analytics for constrained
optimization. It uses implementations that allow students to
explore models and data for the sake of discovery, understanding,
and decision making. Business analytics is about using data and
models to solve various kinds of decision problems. There are three
aspects for those who want to make the most of their analytics:
encoding, solution design, and post-solution analysis. This
textbook addresses all three. Emphasizing the use of constrained
optimization models for decision making, the book concentrates on
post-solution analysis of models. The text focuses on
computationally challenging problems that commonly arise in
business environments. Unique among business analytics texts, it
emphasizes using heuristics for solving difficult optimization
problems important in business practice by making best use of
methods from Computer Science and Operations Research. Furthermore,
case studies and examples illustrate the real-world applications of
these methods. The authors supply examples in Excel (R), GAMS,
MATLAB (R), and OPL. The metaheuristics code is also made available
at the book's website in a documented library of Python modules,
along with data and material for homework exercises. From the
beginning, the authors emphasize analytics and de-emphasize
representation and encoding so students will have plenty to sink
their teeth into regardless of their computer programming
experience.
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