At the core of Industry 4.0, the smart factory integrates automation, mass customization, and self-organization into a highly ...

Abstract: In this paper, a novel general class of optimality criteria is defined and proposed to solve multi-objective optimization problems by using evolutionary algorithms. These criteria, named ...

Abstract: Evolutionary multi-objective optimization algorithms are widely used for solving optimization problems with multiple conflicting objectives. However, basic evolutionary multi-objective ...

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Neel Somani points out that while artificial intelligence may look like it runs on data and algorithms, its real engine is optimization. According to Somani, every breakthrough in the field—from ...

This repository provides the Java (jMetal 4.5), C, Matlab/Octave, and Python implementations of the (at least not synthetic) real-world (RE) problems presented in the following paper: Ryoji Tanabe and ...

Robotic assembly lines serve as a foundational element of modern manufacturing, facilitating the efficient production of high-quality goods. Reducing the energy consumption of robots in these assembly ...

This work considers the problem of learning cooperative policies in multi-agent settings with partially observable and non-stationary environments without a communication channel. We focus on ...

Large language models (LLMs) have revolutionized a wide range of tasks and applications that were previously reliant on manually crafted machine learning (ML) solutions, streamlining through ...

In designing functional biological sequences with machine learning, the activity predictor tends to be inaccurate due to shortage of data. Top ranked sequences are thus unlikely to contain effective ...