Multiobjective optimization

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Multiobjective optimization addresses problems with multiple, often conflicting criteria, prevalent in various fields such as science, engineering, and business. The challenge lies in generating multiple solutions that represent different trade-offs among criteria, known as Pareto optimal or efficient solutions, rather than a single optimal solution. This necessitates a decision maker to provide preference information to identify the most satisfactory solution, which can be integrated at different stages of the optimization process. Expertise in both optimization and decision support is essential in this area. This comprehensive survey stems from the International Seminar on Practical Approaches to Multiobjective Optimization held in Dagstuhl Castle, Germany, in December 2006, where leading experts from diverse fields, including evolutionary multiobjective optimization (EMO), multiple criteria decision making (MCDM), and multiple criteria decision aiding (MCDA), convened. The work offers a unique and thorough overview of the current research and applications in multiobjective optimization, comprising 16 chapters organized into five thematic sections: Basics on Multiobjective Optimization; Recent Interactive and Preference-Based Approaches; Visualization of Solutions; Modelling, Implementation and Applications; and Quality Assessment, Learning, and Future Challenges.