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 ...

Introduction The complex dynamics of the coronavirus disease 2019 (COVID-19) pandemic has made obtaining reliable long-term forecasts of the disease progression difficult. Simple mechanistic models ...

Imagine a town with two widget merchants. Customers prefer cheaper widgets, so the merchants must compete to set the lowest price. Unhappy with their meager profits, they meet one night in a ...

Big Four consulting firm Deloitte just repaid $291,000 to the Australian government after admitting it used ChatGPT to produce a compliance review riddled with errors. The report contained nonexistent ...

Introduction The escalating resistance of microorganisms to antimicrobials poses a significant public health threat. Strategies that use biomarkers to guide antimicrobial therapy—most notably ...

The 3D bin packing problem is a challenging combinatorial optimization problem with numerous real-world applications. In this paper, we present a novel approach for solving this problem by integrating ...

Particle swarm optimization (PSO) algorithm is an optimization technique with remarkable performance for problem solving. The convergence analysis of the method is still in research. This article ...

Finding bipartite matchings is one of the oldest and most well-studied problems in computer science. This problem comes up in many guises, such as when matching donors to recipients for organ ...

People learn adaptively from feedback, but the rate of such learning differs drastically across individuals and contexts. Here, we examine whether this variability reflects differences in what is ...

Large language models have captured the news cycle, but there are many other kinds of machine learning and deep learning with many different use cases. Amid all the hype and hysteria about ChatGPT, ...

Aiming at the poor robustness and adaptability of traditional control methods for different situations, the deep deterministic policy gradient (DDPG) algorithm is improved by designing a hybrid ...