Inside a giant autonomous warehouse, hundreds of robots dart down aisles as they collect and distribute items to fulfill a ...
Practical Application: The authors propose QFI-Informed Mutation (QIm), a heuristic that adapts mutation probabilities using diagonal QFI entries. QIm outperforms uniform and random-restart baselines, ...
Abstract: In scenarios where multiple decision-makers operate within a common decision space, each focusing on their own multi-objective optimization problem (e.g., bargaining games), the problem can ...
Through the looking glass: In a field increasingly defined by quantum experiments and exotic materials, a physics team at Queen's University in Canada has shown that innovation can also come from the ...
Abstract: The manufacturing industry encounters numerous optimization problems, one of which is the optimization of storage location assignment (OSLA) problem in logistics. OSLA is a combinatorial ...
In the field of multi-objective evolutionary optimization, prior studies have largely concentrated on the scalability of objective functions, with relatively less emphasis on the scalability of ...
Want your business to show up in Google’s AI-driven results? The same principles that help you rank in Google Search still matter – but AI introduces new dimensions of context, reputation, and ...
1 School of Mathematics and Statistics, Sichuan University of Science and Engineering, Zigong, China. 2 Institute of Computational Mathematics and Scientific/Engineering Computing, Chinese Academy of ...
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