A self-learning optimizer improved gas production while cutting gas lift usage by 44% across five Delaware basin wells ...

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 ...

Optimal scheduling of battery energy storage system plays crucial part in distributed energy system to provide stability and reduce user costs. Non-linear equipment characteristics (e.g., battery ...

Your code runs without any errors Leave your name, student ID, ETH email address and URL link to demo video in the my-info.json file. April 9: Dear student, we find a minor typo in the README.md. The ...

Meta-heuristic optimization algorithms have seen significant advancements due to their diverse applications in solving complex problems. However, no single algorithm can effectively solve all ...

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Abstract: We analyze three permutation-based combinatorial optimization problems in Fourier space, namely, the quadratic assignment problem, the linear ordering problem (LOP), and the symmetric and ...

In the realm of decision-making, optimization plays a pivotal role making (Albright & Winston, 2020). Linear programming, particularly the Simplex Method, is a fundamental technique for optimizing a ...

A framework based on advanced AI techniques can solve complex, computationally intensive problems faster and in a more more scalable way than state-of-the-art methods, according to a study led by ...

Abstract: It is very challenging to autonomously generate algorithms suitable for constrained multiobjective optimization problems due to the diverse performance of existing algorithms. In this ...

Energy systems models are invaluable planning tools. However, these tools typically produce singular “cost-optimal” solutions that can overlook other solutions that may be more viable when considering ...