ItemConference Paper

Deep Learning in Project Planning and Scheduling

Title
Deep Learning in Project Planning and Scheduling
Creator
Shetty, Keerthi; Gautam, Kamlesh Kumar; Rupani, Jigar; Khan, Shakir; Sreedevi, Vaitla; Dhawale, Sagar Digambar
Description
Controlling construction projects requires careful planning, and the most popular modelling techniques are the discrete-event simulator (DES), linear schedule (LS), and the critical path method (CPM). DES techniques, however, may become laborious and struggle to appropriately represent decision possibilities as complexity and restrictions increase. Through the reinforcement learning methods, deep learning-based artificial intelligence (AI) may be a viable substitute, enabling a quicker evaluation and suggestion of planning solutions for intricate building projects. This study investigates if artificial intelligence (AI) can replace DES in Insight, an illustrated constraint-based procedure planning tool for production and building. In the study, the difficulties of integrating AI into planning for building are discussed, along with the process modifications required to support deep learning techniques. Enhanced schedule, expenses, and efficiency in operation result from early planning of projects, which also balances conflicting project requirements. The planning of modern building projects is suggested to use a new conceptual methodology. 2025 IEEE.
Source
2025 World Skills Conference on Universal Data Analytics and Sciences, WorldSUAS 2025;
Date
01-01-2025
Publisher
Institute of Electrical and Electronics Engineers Inc.
Subject
AI; critical path method (CPM); Deep Learning; linear scheduling (LS); Machine learning (ML)
Coverage
Shetty K., Nitte (Deemed to Be University), NMAM Institute of Technology, Department of MCA, Udupi, India; Gautam K.K., Mewar Institute of Management, Vasundhara, Department of Computer Science, Uttar Pradesh, Ghaziabad, India; Rupani J., Christ University, School of Business and Management, India; Khan S., Imam Mohammad Ibn Saud Islamic University (IMSIU), College of Computer and Information Sciences, Riyadh, 11432, Saudi Arabia, Chandigarh University, University Centre for Research and Development, Department of Computer Science and Engineering, Mohali, 140413, India; Sreedevi V., Malla Reddy Engineering College (A), Maisammaguda, Kompally, Department of CSE, Telagana State, Secunderabad, 500100, India; Dhawale S.D., Ajeenkya D y Patil School of Engineering, Lohegaon, Department of Electronics & Telecommunication Engineering, Maharashtra, Pune, 412105, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISBN: 979-833153925-2;
Format
online
Language
English
Type
Conference paper

Citation

Shetty, Keerthi; Gautam, Kamlesh Kumar; Rupani, Jigar; Khan, Shakir; Sreedevi, Vaitla; Dhawale, Sagar Digambar, “Deep Learning in Project Planning and Scheduling,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/26225.

Output Formats