Management Science with Python (Paperback)

Minjun Kim

ISBN 13: 9798310489493

Published by Independently Published, 2025

About this Item

Paperback. Blending classical management science approaches with real-world Python exercises, each concept is introduced in a hands-on manner. Topics span sensitivity analysis, breakeven analysis, linear programming, simulation, dynamic programming, network models, PERT/CPM, Project management and more all illustrated with step-by-step examples. Industry use cases in supply chain and project management underscore how these solutions transform everyday operations. College students and professional managers will discover how to optimize decisions, handle uncertainty, and simulate complex systems throughout tailored Python examples. Readers can tackle real scenarios like inventory planning or critical path scheduling, bridging theory with immediate application. Emphasizing approachable language and practical demonstrations, this textbook supports robust course curricula, guided research projects, or self-study experiences that equip learners with modern problem-solving skills. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Seller Inventory # 9798310489493

Bibliographic Details

• Title: Management Science with Python (Paperback)
• Publisher: Independently Published
• Publication Date: 2025
• Language: English
• ISBN 13: 9798310489493
• Binding: Paperback
• Condition: new

About this title

Synopsis

Blending classical management science approaches with real-world Python exercises, each concept is introduced in a hands-on manner. Topics span sensitivity analysis, breakeven analysis, linear programming, simulation, dynamic programming, network models, PERT/CPM, Project management and more all illustrated with step-by-step examples. Industry use cases in supply chain and project management underscore how these solutions transform everyday operations. College students and professional managers will discover how to optimize decisions, handle uncertainty, and simulate complex systems throughout tailored Python examples. Readers can tackle real scenarios like inventory planning or critical path scheduling, bridging theory with immediate application. Emphasizing approachable language and practical demonstrations, this textbook supports robust course curricula, guided research projects, or self-study experiences that equip learners with modern problem-solving skills.