Integrating machine learning and mathematical optimization for job shop scheduling

A Liu, PB Luh, K Sun, MA Bragin… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Job-shop scheduling is an important but difficult combinatorial optimization problem for low-
volume and high-variety manufacturing, with solutions required to be obtained quickly at the …

A Review of Integrated Optimization Method of Batch Planning and Scheduling for Steelmaking-Continuous Casting-Hot Rolling Production Under Uncertain …

L Sun, X Hao, Y Li, J Xue… - Complex System …, 2024 - ieeexplore.ieee.org
The integrated process of steelmaking, continuous casting, and hot rolling (SM-CC-HR)
covers the entire process from refining liquid steel to manufacturing semi-finished steel …

A novel optimization approach for sub-hourly unit commitment with large numbers of units and virtual transactions

J Wu, PB Luh, Y Chen, MA Bragin… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Unit Commitment (UC) is an important problem in power system operations. It is traditionally
planned for 24 hours with one-hour time intervals. To accommodate the increasing net-load …

Apply ordinal optimization to optimize the job-shop scheduling under uncertain processing times

SC Horng, SS Lin - Arabian Journal for Science and Engineering, 2022 - Springer
The job shop scheduling problem is generally divided into two types according to production
environments, the job shop scheduling problem with deterministic processing times and the …

[HTML][HTML] Hierarchical distributed optimization of constraint-coupled convex and mixed-integer programs using approximations of the dual function

V Yfantis, S Wenzel, A Wagner, M Ruskowski… - EURO Journal on …, 2023 - Elsevier
In this paper, two new algorithms for dual decomposition-based distributed optimization are
presented. Both algorithms rely on the quadratic approximation of the dual function of the …

Incorporate seagull optimization into ordinal optimization for solving the constrained binary simulation optimization problems

SC Horng, SS Lin - The Journal of Supercomputing, 2023 - Springer
Constrained binary simulation optimization problems (CBSOP) are optimization problems
with binary variables and stochastic objective function subject to given constraints. Solving …

A novel solar radio spectrogram encryption algorithm based on parameter variable chaotic systems and DNA dynamic encoding

Y Shen, T Zou, L Zhang, Z Wu, Y Su, F Yan - Physica Scripta, 2022 - iopscience.iop.org
Considering that chaotic systems are highly sensitive to parameters, we design two new
parameter variable chaotic systems by constructing parameter perturbation items. These …

A robust optimization approach for steeling-continuous casting charge batch planning with uncertain slab weight

C Li, L Sun - Journal of Process Control, 2024 - Elsevier
The volatility of slab weight in steelmaking-continuous casting (SCC) production, attributed
to factors such as flexible order demand, is addressed in this paper. A robust optimization …

Simultaneous optimization of task allocation and path planning using mixed-integer programming for time and capacity constrained multi-agent pickup and delivery

T Okubo, M Takahashi - 2022 22nd International Conference …, 2022 - ieeexplore.ieee.org
Lately, there has been a need to improve the efficiency of material movements within
factories and multi-agents are required to perform these tasks. In this study, graphical …

Multi-Agent Action Graph Based Task Allocation and Path Planning Considering Changes in Environment

T Okubo, M Takahashi - IEEE Access, 2023 - ieeexplore.ieee.org
Task allocation and path planning considering changes in the mobility of robots in the
environment allows the robots to efficiently execute tasks with smaller travel times. A lunar …