Solving complex optimization problems is central to many modern technologies, from logistics and financial modeling to chip ...

Combinatorial optimisation for knapsack problems addresses the challenge of selecting discrete items to maximise value under capacity constraints. Such problems are central to resource allocation, ...

To continue reading this content, please enable JavaScript in your browser settings and refresh this page. Preview this article 1 min Knapsack raised $10 million from ...

Getting design and engineering teams on the same page about what digital product to create and how to build it continues to be a challenge. A lot of companies find themselves dealing with scattered ...

Abstract: The knapsack problem is a classic NP-hard optimization challenge with wide-ranging applications in computer science, such as resource allocation. While several variants have been developed, ...

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You may have noticed that Smokey Bear has changed his tagline. In fact, it’s been different for years now, but with current news stories, it catches the ear differently. Many of us grew up with Smokey ...

Abstract: The quadratic multiple knapsack problem (QMKP) is a well-studied problem in operations research. This problem involves selecting a subset of items that maximizes the linear and quadratic ...

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 ...

Computer-generated holography (CGH) provides an approach to digitally modulate a given wavefront. This technology, partly inherited from optical holography and partly advanced by the progress of ...