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®, GAMS, MATLAB®, 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.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Steven Orla Kimbrough, The Wharton School, University of Pennsylvania, Philadelphia, USA
Hoong Chuin Lau, School of Information Systems, Singapore Management University, Singapore
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Anbieter: GreatBookPrices, Columbia, MD, USA
Zustand: As New. Unread book in perfect condition. Bestandsnummer des Verkäufers 48136615
Anzahl: 10 verfügbar
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
Zustand: New. Bestandsnummer des Verkäufers 410728991
Anzahl: 3 verfügbar
Anbieter: GreatBookPrices, Columbia, MD, USA
Zustand: New. Bestandsnummer des Verkäufers 48136615-n
Anzahl: 10 verfügbar
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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®, GAMS, MATLAB®, 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. 330 pp. Englisch. Bestandsnummer des Verkäufers 9781032922713
Anzahl: 2 verfügbar
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
Zustand: As New. Unread book in perfect condition. Bestandsnummer des Verkäufers 48136615
Anzahl: 10 verfügbar
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
Zustand: New. Bestandsnummer des Verkäufers 48136615-n
Anzahl: 10 verfügbar
Anbieter: THE SAINT BOOKSTORE, Southport, Vereinigtes Königreich
Paperback / softback. Zustand: New. New copy - Usually dispatched within 4 working days. Bestandsnummer des Verkäufers B9781032922713
Anzahl: 1 verfügbar
Anbieter: Books Puddle, New York, NY, USA
Zustand: New. Bestandsnummer des Verkäufers 26403473856
Anzahl: 3 verfügbar
Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
Zustand: New. Bestandsnummer des Verkäufers 18403473866
Anzahl: 3 verfügbar
Anbieter: moluna, Greven, Deutschland
Zustand: New. Steven Orla Kimbrough, The Wharton School, University of Pennsylvania, Philadelphia, USAHoong Chuin Lau, School of Information Systems, Singapore Management University, SingaporeBusiness Analyti. Bestandsnummer des Verkäufers 1800936623
Anzahl: Mehr als 20 verfügbar