An efficient Q-learning integrated multi-objective hyper-heuristic approach for hybrid flow shop scheduling problems with lot streaming
Efficient scheduling in flow shop environments with lot streaming remains a critical
challenge in various industrial settings, necessitating innovative approaches to optimize …
challenge in various industrial settings, necessitating innovative approaches to optimize …
Dynamic path planning for mobile robots based on artificial potential field enhanced improved multiobjective snake optimization (APF‐IMOSO)
Q Li, Q Ma, X Weng - Journal of Field Robotics, 2024 - Wiley Online Library
With the widespread adoption of mobile robots, effective path planning has become
increasingly critical. Although traditional search methods have been extensively utilized …
increasingly critical. Although traditional search methods have been extensively utilized …
A cascading elimination-based evolutionary algorithm with variable classification mutation for many-objective optimization
W Zhang, J Liu, W Yang, S Tan - Information Sciences, 2024 - Elsevier
Many-objective evolutionary algorithms have gained significant achievements over the
years. However, the difficulty in balancing convergence and diversity of the population …
years. However, the difficulty in balancing convergence and diversity of the population …
A decomposition-based many-objective evolutionary algorithm with Q-learning guide weight vectors update
HJ Zhang, Y Dai - Expert Systems with Applications, 2025 - Elsevier
When dealing with regular, simple Pareto fronts (PFs), the decomposition-based multi-
objective optimization algorithm (MOEA/D) performs well by presetting a set of uniformly …
objective optimization algorithm (MOEA/D) performs well by presetting a set of uniformly …
ERLNEIL-MDP: Evolutionary reinforcement learning with novelty-driven exploration for medical data processing
The rapid growth of medical data presents opportunities and challenges for healthcare
professionals and researchers. To effectively process and analyze this complex and …
professionals and researchers. To effectively process and analyze this complex and …
Many-Objective Ant Lion Optimizer (MaOALO): A new many-objective optimizer with its engineering applications
Many-objective optimization (MaO) is an important aspect of engineering scenarios. In many-
objective optimization algorithms (MaOAs), a key challenge is to strike a balance between …
objective optimization algorithms (MaOAs), a key challenge is to strike a balance between …
A hybrid grey wolf optimizer for engineering design problems
S Chen, J Zheng - Journal of Combinatorial Optimization, 2024 - Springer
Grey wolf optimizer (GWO) is one of the most popular metaheuristics, and it has been
presented as highly competitive with other comparison methods. However, the basic GWO …
presented as highly competitive with other comparison methods. However, the basic GWO …
Two-stage particle swarm optimization with dual-indicator fusion ranking for multi-objective problems
Elite solutions guiding population evolution are often used as one of main ideas to improve
the performance of multi-objective particle swarm optimization (MOPSO). However, in most …
the performance of multi-objective particle swarm optimization (MOPSO). However, in most …
Reinforcement learning-assisted particle swarm algorithm for effluent scheduling problem with an influent estimation of WWTP
HAN HongGui, XU ZiAng, W JingJing - Swarm and Evolutionary …, 2025 - Elsevier
Effluent scheduling of wastewater treatment process (WWTP) is essential to ensure
compliance with regulatory standards regarding effluent quality. Through the integration of …
compliance with regulatory standards regarding effluent quality. Through the integration of …
Solving Orienteering Problems by Hybridizing Evolutionary Algorithm and Deep Reinforcement Learning
The orienteering problem (OP) is widely applied in real life. However, as the scale of real-
world problem scenarios grows quickly, traditional exact, heuristics and learning-based …
world problem scenarios grows quickly, traditional exact, heuristics and learning-based …