Combinatorial optimization problems are often encountered in real-world applications, including logistics, scheduling and ...
Combinatorial optimization problems are encountered often in various real-world applications, including logistics, scheduling, and network design ...
A deep reinforcement learning framework optimizes silicon-based photonic crystal fiber modulators, achieving ultra-low ...
Water distribution network (WDN) optimization has received special attention from various technicians and researchers, mainly due to its high costs of implementation, operation and maintenance.
Abstract: The Tardy/Lost (TL) penalties scheduling is a discrete optimization problem. TL scheduling problem is an NP-hard problem. As a result, proposing an optimization algorithm to handle this ...
Abstract: A discrete particle swarm optimization algorithm with adaptive inertia weight (DPSO-AIW) is proposed to solve the multiobjective Flexible Job-shop Scheduling Problem. The algorithm uses a ...
The integration of multi-modal learning with large-scale models has become a transformative force in the fields of artificial intelligence and neurorobotics. Human perception naturally relies on the ...
In this paper a new hybrid glowworm swarm algorithm (SAGSO) for solving structural optimization problems is presented. The structure proposed to be optimized here is a simply-supported concrete I-beam ...
United Nations Sustainable Development Goal 7 is about ensuring access to clean and affordable energy, which is a key factor in the development of society. The power generation sector majorly consists ...
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