The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

Genetic algorithms (GA) are one of the efficient methods for various NP-hard combinatorial optimization problems. And previous research has also proposed hybrid genetic algorithms (HGA) that combine ...

Using an advanced Monte Carlo method, Caltech researchers found a way to tame the infinite complexity of Feynman diagrams and solve the long-standing polaron problem, unlocking deeper understanding of ...

A Python implementation of a branch-and-bound approach (plus a simple greedy heuristic) to solve a variation of the multiple knapsack problem where items have both individual and pairwise benefits.

Right now, quantum computers are small and error-prone compared to where they’ll likely be in a few years. Even within those limitations, however, there have been regular claims that the hardware can ...

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Institute of Logistics Science and Engineering of Shanghai Maritime University, Pudong, China Introduction: This study addresses the joint scheduling optimization of continuous berths and quay cranes ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. We present an artificial intelligence-guided approach to design durable and chemically ...

Abstract: The genetic algorithms are a well-known family of high-performance probabilistic algorithms. In this paper, we explore the possibility of using the genetic algorithm for the Knapsack problem ...