Results 81 to 90 of about 9,168 (188)
An Efficient Optimization Algorithm for Resource-Constrained Steelmaking Scheduling Problems
IEEE Access, 2018 In this paper, we address the steelmaking scheduling problems with multiple constrained resources. The objective is to minimize the maximum completion time. We consider the continuous casting constraint and resource constraints simultaneously.
Junqing Li +5 more
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Where Should We Place LiDARs on the Autonomous Vehicle? - An Optimal Design Approach
, 2019 Autonomous vehicle manufacturers recognize that LiDAR provides accurate 3D views and precise distance measures under highly uncertain driving conditions. Its practical implementation, however, remains costly.
Arief, Mansur, Liu, Zuxin, Zhao, Ding
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Research on Three‐Dimensional Autonomous Obstacle Avoidance Path Planning Methods for UAVs
Transactions on Emerging Telecommunications Technologies, Volume 37, Issue 2, February 2026.This study presents a three‐dimensional autonomous obstacle‐avoidance path planning method for unmanned aerial vehicles (UAVs) based on a deep reinforcement learning (DRL)‐enhanced Mayfly Algorithm. The traditional Mayfly Algorithm suffers from issues such as random initial population generation and slow convergence.
Chong Wu, Hao Cheng, Hua Wang
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Artificial Flora (AF) Optimization Algorithm
Applied Sciences, 2018 Inspired by the process of migration and reproduction of flora, this paper proposes a novel artificial flora (AF) algorithm. This algorithm can be used to solve some complex, non-linear, discrete optimization problems.
Long Cheng, Xue-han Wu, Yan Wang
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Studies in Applied Mathematics, Volume 156, Issue 2, February 2026.ABSTRACT In this paper, we propose a decompositional (phase‐wise split) approach to solve a two‐dimensional, two‐phase (solid and liquid, say), nonlinear inverse Stefan problem. The first step is to approximate the unknown moving boundary between the two phases and the Stefan condition on that boundary using the overspecified boundary and initial data ...
Gujji Murali Mohan Reddy +2 more
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Discrete and Continuous Optimization Based on Hierarchical Artificial Bee Colony Optimizer
Journal of Applied Mathematics, 2014 This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization (HABC), to tackle complex high-dimensional problems.
Lianbo Ma +5 more
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Asian Journal of Control, Volume 28, Issue 1, Page 20-33, January 2026.Abstract This study presents a non‐iterative tuning technique for a linear fractional‐order (FO) controller, based on the integral of the time‐weighted absolute error (ITAE) criterion. Minimizing the ITAE is a traditional approach for tuning FO controllers. This technique reduces the over/undershoot and suppresses the steady‐state error. In contrast to
Ansei Yonezawa +4 more
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Swarm intelligence for scheduling: a review [PDF]
, 2013 Swarm Intelligence generally refers to a problem-solving ability that emerges from the interaction of simple information-processing units. The concept of Swarm suggests multiplicity, distribution, stochasticity, randomness, and messiness.
Madureira, Ana Maria +2 more
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Discrete optimum design of truss structures using artificial bee colony algorithm
Structural and Multidisciplinary Optimization, 2010 Over the past few years, swarm intelligence based optimization techniques such as ant colony optimization and particle swarm optimization have received considerable attention from engineering researchers and practitioners. These algorithms have been used in the solution of various engineering problems.
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Ensemble Kalman filter in latent space using a variational autoencoder pair
Quarterly Journal of the Royal Meteorological Society, Volume 152, Issue 775, January 2026 Part B.The use of the ensemble Kalman filter (EnKF) in strongly nonlinear or constrained atmospheric, oceanographic, or sea‐ice models can be challenging. Applying the EnKF in the latent space of a variational autoencoder (VAE) ensures that the ensemble members satisfy the balances and constraints present in the model.
Ivo Pasmans +4 more
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