A hyperheuristic with Q-learning for the multiobjective energy-efficient distributed blocking flow shop scheduling problem
F Zhao, S Di, L Wang - IEEE Transactions on Cybernetics, 2022 - ieeexplore.ieee.org
Carbon peaking and carbon neutrality, which are the significant national strategy for
sustainable development, have attracted considerable attention from production enterprises …
sustainable development, have attracted considerable attention from production enterprises …
Large language models as evolutionary optimizers
Evolutionary algorithms (EAs) have achieved remarkable success in tackling complex
combinatorial optimization problems. However, EAs often demand carefully-designed …
combinatorial optimization problems. However, EAs often demand carefully-designed …
Towards green smart cities using Internet of Things and optimization algorithms: A systematic and bibliometric review
P He, N Almasifar, A Mehbodniya, D Javaheri… - … Informatics and Systems, 2022 - Elsevier
Energy efficiency is an important concern that the scientific community and society will have
to deal with in the coming years. Power-efficient structures and effective energy resource …
to deal with in the coming years. Power-efficient structures and effective energy resource …
Distributed scheduling problems in intelligent manufacturing systems
Currently, manufacturing enterprises face increasingly fierce market competition due to the
various demands of customers and the rapid development of economic globalization …
various demands of customers and the rapid development of economic globalization …
Knowledge-based reinforcement learning and estimation of distribution algorithm for flexible job shop scheduling problem
Y Du, J Li, X Chen, P Duan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Inthis study, a flexible job shop scheduling problem with time-of-use electricity price
constraint is considered. The problem includes machine processing speed, setup time, idle …
constraint is considered. The problem includes machine processing speed, setup time, idle …
A cooperative memetic algorithm with learning-based agent for energy-aware distributed hybrid flow-shop scheduling
With increasing environmental awareness and energy requirement, sustainable
manufacturing has attracted growing attention. Meanwhile, distributed manufacturing …
manufacturing has attracted growing attention. Meanwhile, distributed manufacturing …
A cooperative memetic algorithm with feedback for the energy-aware distributed flow-shops with flexible assembly scheduling
With economic globalization and increasingly concerned sustainable manufacturing, energy-
aware distributed scheduling and flexible assembly are significant to optimize global supply …
aware distributed scheduling and flexible assembly are significant to optimize global supply …
A learning-driven multi-objective cooperative artificial bee colony algorithm for distributed flexible job shop scheduling problems with preventive maintenance and …
In recent years, distributed production scheduling problems receive much attention from
both scholars and practicers. Nevertheless, existing research on such problems commonly …
both scholars and practicers. Nevertheless, existing research on such problems commonly …
Heuristic and metaheuristic methods for the parallel unrelated machines scheduling problem: a survey
M Ɖurasević, D Jakobović - Artificial Intelligence Review, 2023 - Springer
Scheduling has an immense effect on various areas of human lives, be it though its
application in manufacturing and production industry, transportation, workforce allocation, or …
application in manufacturing and production industry, transportation, workforce allocation, or …
Recent trends in distributed production network scheduling problem
N Bagheri Rad, J Behnamian - Artificial Intelligence Review, 2022 - Springer
The complex problems in the real world, an increase in competition among producers, the
advancements in equipment and manufacturing products, the high cost of factory equipment …
advancements in equipment and manufacturing products, the high cost of factory equipment …