Multi-Objective Optimization in Practice
Stakeholder-Driven Methods for Real-World Decision Support
Created by AhmedMost optimization practitioners believe that sophisticated algorithms are the key to solving multi-objective problems effectively. This assumption leads to elegant mathematical solutions that fail spectacularly when applied to real-world scenarios with multiple stakeholders and conflicting objectives. The reality is that successful multi-objective optimization depends far more on proper problem formulation, stakeholder engagement, and systematic preference elicitation than on algorithmic complexity. This comprehensive guide bridges the gap between theoretical optimization and practical implementation, showing you how to develop weighted sum methods that actually work with real stakeholders and create decision support systems that deliver actionable results. You'll discover how to formulate multi-objective problems that capture the true essence of real-world decision scenarios, engage stakeholders effectively to elicit meaningful preferences, and handle the messy constraints that textbooks rarely address. Through detailed coverage of interactive decision support systems, hybrid optimization approaches, and goal programming applications, you'll learn to build tools that stakeholders trust and use. Drawing from extensive transportation case studies and other practical applications, this book provides the frameworks, techniques, and insights you need to move beyond academic exercises and solve the complex multi-objective optimization challenges that define modern decision-making environments.
Est. Length
284 pages (14 chapters)
Language
English
Publication date
Oct 6, 2025
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