Task Scheduling Optimization from a Tensor Network Perspective

• URL: http://arxiv.org/abs/2311.10433v2
• Date: Thu, 20 Jun 2024 10:39:09 GMT
• Title: Task Scheduling Optimization from a Tensor Network Perspective
• Authors: Alejandro Mata Ali, Iñigo Perez Delgado, Beatriz García Markaida, Aitor Moreno Fdez. de Leceta,
• Abstract summary: We present a novel method for task optimization in industrial plants using quantum-inspired tensor network technology. We simulate a quantum system with all possible combinations, perform an imaginary time evolution and a series of projections to satisfy the constraints.
• Score: 41.94295877935867
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We present a novel method for task optimization in industrial plants using quantum-inspired tensor network technology. This method allows us to obtain the best possible combination of tasks on a set of machines with a set of constraints without having to evaluate all possible combinations. We simulate a quantum system with all possible combinations, perform an imaginary time evolution and a series of projections to satisfy the constraints. We improve its scalability by means of a compression method, an iterative algorithm, and a genetic algorithm, and show the results obtained on simulated cases.

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