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Iterated greedy algorithms for flow-shop scheduling problems: A tutorial
ZY Zhao, MC Zhou, SX Liu - IEEE Transactions on Automation …, 2021 - ieeexplore.ieee.org
An iterated greedy algorithm (IGA) is a simple and powerful heuristic algorithm. It is widely
used to solve flow-shop scheduling problems (FSPs), an important branch of production …
used to solve flow-shop scheduling problems (FSPs), an important branch of production …
A review of prospects and opportunities in disassembly with human–robot collaboration
Product disassembly plays a crucial role in the recycling, remanufacturing, and reuse of end-
of-use (EoU) products. However, the current manual disassembly process is inefficient due …
of-use (EoU) products. However, the current manual disassembly process is inefficient due …
Energy-optimized partial computation offloading in mobile-edge computing with genetic simulated-annealing-based particle swarm optimization
Smart mobile devices (SMDs) can meet users' high expectations by executing computational
intensive applications but they only have limited resources, including CPU, memory, battery …
intensive applications but they only have limited resources, including CPU, memory, battery …
Reinforcement learning for disassembly system optimization problems: A survey
The disassembly complexity of end-of-life products increases continuously. Traditional
methods are facing difficulties in solving the decision-making and control problems of …
methods are facing difficulties in solving the decision-making and control problems of …
Stochastic hybrid discrete grey wolf optimizer for multi-objective disassembly sequencing and line balancing planning in disassembling multiple products
Recycling, reusing, and remanufacturing of end-of-life (EOL) products have been receiving
increasing attention. They effectively preserve the ecological environment and promote the …
increasing attention. They effectively preserve the ecological environment and promote the …
A machine learning and genetic algorithm-based method for predicting width deviation of hot-rolled strip in steel production systems
Width deviation is an important metric for evaluating the quality of a hot-rolled strip in steel
production systems. This paper considers a width deviation prediction problem and …
production systems. This paper considers a width deviation prediction problem and …
Path planning method with improved artificial potential field—a reinforcement learning perspective
The artificial potential field approach is an efficient path planning method. However, to deal
with the local-stable-point problem in complex environments, it needs to modify the potential …
with the local-stable-point problem in complex environments, it needs to modify the potential …
Dual-objective mixed integer linear program and memetic algorithm for an industrial group scheduling problem
Z Zhao, S Liu, MC Zhou… - IEEE/CAA Journal of …, 2020 - ieeexplore.ieee.org
Group scheduling problems have attracted much attention owing to their many practical
applications. This work proposes a new bi-objective serial-batch group scheduling problem …
applications. This work proposes a new bi-objective serial-batch group scheduling problem …
Disassembly sequence planning: a survey
It is well-recognized that obsolete or discarded products can cause serious environmental
pollution if they are poorly be handled. They contain reusable resource that can be recycled …
pollution if they are poorly be handled. They contain reusable resource that can be recycled …
A novel Q-learning based variable neighborhood iterative search algorithm for solving disassembly line scheduling problems
This paper addresses disassembly line scheduling problems (DLSP) to minimize the
smoothing index with the workstation number threshold. First, a mathematical model is …
smoothing index with the workstation number threshold. First, a mathematical model is …