Automating look-ahead schedule generation for construction using linked-data based constraint checking and reinforcement learning-Reference-Cited by-同舟云学术

Automating look-ahead schedule generation for construction using linked-data based constraint checking and reinforcement learning

Published:2022-02 Issue: Volume:134 Page:104069
ISSN:0926-5805
Container-title:Automation in Construction
language:en
Short-container-title:Automation in Construction

Author:

Soman Ranjith K.,Molina-Solana Miguel

Publisher

Elsevier BV

Subject

Building and Construction,Civil and Structural Engineering,Control and Systems Engineering

Reference113 articles.

1. Rethinking lookahead planning to optimize construction workflow;Hamzeh;Lean Construct. J.,2012

2. Resource unconstrained and constrained project scheduling problems and practices in a multiproject environment;Kannimuthu;Adv. Civ. Eng.,2018

3. Scheduling of large, complex, and constrained construction projects - an exploration of LPS application;Lindhard;Int. J. Proj. Org. Manag.,2014

4. A method to automate look-ahead schedule (LAS) generation for the finishing phase of construction projects;Dong;Autom. Constr.,2013

5. Operational Efficiency Frontier: Visualizing, Manipulating, and Navigating the Construction Scheduling State Space with Precedence, Discrete, and Disjunctive Constraints;Morkos,2014

Cited by 25 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Automated construction scheduling using deep reinforcement learning with valid action sampling;Automation in Construction;2024-10

2. Smart Techniques Promoting Sustainability in Construction Engineering and Management;Engineering;2024-09

3. Proposing a Lean-Optimized Scheduling Model of Mixed-Flow Prefabricated Component Production in Off-Site Construction;Journal of Construction Engineering and Management;2024-08

4. Dynamic Real-Time Optimization of Modular Unit Allocation to Off-Site Facilities in Postdisaster Reconstruction Using Deep Reinforcement Learning;Journal of Management in Engineering;2024-07

5. Simulation of autonomous resource allocation through deep reinforcement learning-based portfolio-project integration;Automation in Construction;2024-06