Results 81 to 90 of about 13,809 (278)

Reinforcement Learning‐Assisted Meta‐Heuristics for Scheduling Job Shops With Material Handling Robots

open access: yesIET Collaborative Intelligent Manufacturing, Volume 8, Issue 1, January/December 2026.
This study addresses an integrated job shop scheduling problem with material handling robots, aiming to minimise the maximum completion time. Three meta‐heuristics, seven local search strategies and two reinforcement learning algorithms are proposed to solve the problems.
Qi Jia   +3 more
wiley   +1 more source

Efficient Task Scheduling and Load Balancing in Fog Computing for Crucial Healthcare Through Deep Reinforcement Learning

open access: yesIEEE Access
In healthcare, real-time decision making is crucial for ensuring timely and accurate patient care. However, traditional computing infrastructures, with their wide ranging capabilities, suffer from inherent latency, which compromises the efficiency of ...
Prashanth Choppara, Bommareddy Lokesh
doaj   +1 more source

Time‐ and Behaviour‐Preserving Execution of Determinate Supervisory Control

open access: yesIET Cyber-Physical Systems: Theory &Applications, Volume 11, Issue 1, January/December 2026.
The activity framework is a model‐based framework incorporating a model of activities with determinate timing and behaviour, and a strong mathematical foundation based on max‐plus algebra that allows efficient timing analysis and optimisation of CPS. Preserving the specified behaviour and the model‐predicted timing in an implementation is challenging ...
Alireza Mohamadkhani   +3 more
wiley   +1 more source

Flexible Scheduling for Large‐Scale Autonomous Driving Trucks in Open‐Pit Mining With Reinforcement Learning‐Assisted Evolutionary Programming

open access: yesIET Cyber-Systems and Robotics, Volume 8, Issue 1, January/December 2026.
ABSTRACT Deployment of autonomous driving trucks (ADTs) in open‐pit mining enables more flexible transport operations than human‐driven trucks; but this flexibility significantly expands the scheduling search space and makes it more difficult to find near‐optimal solutions on large scales.
Rentao Sun   +3 more
wiley   +1 more source

The complexity of makespan minimization for pipeline transportation

open access: yesTheoretical Computer Science, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ruy Luiz Milidiú   +2 more
openaire   +2 more sources

Railway scheduling reduces the expected project makespan. [PDF]

open access: yes
The Critical Chain Scheduling and Buffer Management (CC/BM) methodology, proposed by Goldratt (1997), introduced the concepts of feeding buffers, project buffers and resource buffers as well as the roadrunner mentality.
Demeulemeester, Erik, Tian, Wendi
core  

A greedy algorithm for computing finite-makespan controllable sublanguages

open access: yes, 2012
The Ramadge-Wonham supervisory control paradigm has been shown effective in dealing with logic control. Nevertheless, time-related performance is always one of the major concerns in industry.
Rong Su, Su, Rong.
core   +1 more source

A Novel Heterogeneous Graph Attention‐Enhanced Deep Reinforcement Learning‐Based Framework for Production Scheduling in Cloud Manufacturing

open access: yesElectronics Letters, Volume 62, Issue 1, January/December 2026.
This paper introduces a heterogeneous graph attention‐enhanced deep reinforcement learning‐based scheduling framework designed to instantaneously generate high‐quality production plans for production scheduling in cloud manufacturing. The proposed framework has been tested on multiple public datasets and industrial instances, and compared against ...
Shiduo Ning   +5 more
wiley   +1 more source

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