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Off-year elections might hold more lessons for Republicans than Democrats. By Jess Bidgood Victorious Democrats spent Wednesday eagerly pointing to all their midterm lessons from the previous night.

Abstract: Dynamic constrained multiobjective optimization problems (DCMOPs) involve complex changes in objective functions and constraints over time. These changes challenge most existing algorithms ...

A line of engineering research seeks to develop computers that can tackle a class of challenges called combinatorial optimization problems. These are common in real-world applications such as ...

Ad tech is obsessed with optimization. Every signal, platform, algorithm, clean room, or assistant, is pitched as a way to bring brands closer to consumers. But what if the opposite is happening? What ...

It’s been difficult to find important questions that quantum computers can answer faster than classical machines, but a new algorithm appears to do it for some critical optimization tasks. For ...

The rise of AI, graphic processing, combinatorial optimization and other data-intensive applications has resulted in data-processing bottlenecks, as ever greater amounts of data must be shuttled back ...

Abstract: In this paper, we focus on the idea of integral designing of problems/methods/distances in metaheuristics for combinatorial optimization problems. As a practical example of the above idea, ...