Challenges Applying Dynamic Multi-objective Optimisation Algorithms to Real-World Problems
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Smith, Alice E
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Abstract
Many optimisation problems have multiple conflicting goals, where at least one objective and/or constraint is dynamic in nature. These problems are referred to as dynamic multi-objective optimisation problems (DMOOPs). Most of the research in the field of dynamic multi-objective optimisation (DMOO) focuses on the development of new algorithms. However, there still remain a number of challenges to be addressed before the algorithms can be efficiently applied to real-world DMOO problems (RWPs). This chapter firstly presents a taxonomy of dynamic multi-objective optimisation (DMOO) RWPs and highlights the characteristics of these problems. These characteristics bring to light the challenges that should still be addressed when applying DMOO algorithms to RWPs.
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Women in Computational Intelligence: Key Advances and Perspectives on Emerging Topics
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VII
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Evolutionary computation
Satisfiability and optimisation
Planning and decision making
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Helbig, M, Challenges Applying Dynamic Multi-objective Optimisation Algorithms to Real-World Problems, Women in Computational Intelligence Key Advances and Perspectives on Emerging Topics, 2021, VII