IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Hybrid Meta-Heuristics Based System for Dynamic Scheduling

Hybrid Meta-Heuristics Based System for Dynamic Scheduling
View Sample PDF
Author(s): Ana Maria Madureira (Polytechnic Institute of Porto, Portugal)
Copyright: 2009
Pages: 7
Source title: Encyclopedia of Artificial Intelligence
Source Author(s)/Editor(s): Juan Ramón Rabuñal Dopico (University of A Coruña, Spain), Julian Dorado (University of A Coruña, Spain)and Alejandro Pazos (University of A Coruña, Spain)
DOI: 10.4018/978-1-59904-849-9.ch126

Purchase

View Hybrid Meta-Heuristics Based System for Dynamic Scheduling on the publisher's website for pricing and purchasing information.

Abstract

The complexity of current computer systems has led the software engineering, distributed systems and management communities to look for inspiration in diverse fields, e.g. robotics, artificial intelligence or biology, to find new ways of designing and managing systems. Hybridization and combination of different approaches seems to be a promising research field of computational intelligence focusing on the development of the next generation of intelligent systems. A manufacturing system has a natural dynamic nature observed through several kinds of random occurrences and perturbations on working conditions and requirements over time. For this kind of environment it is important the ability to efficient and effectively adapt, on a continuous basis, existing schedules according to the referred disturbances, keeping performance levels. The application of Meta-Heuristics to the resolution of this class of dynamic scheduling problems seems really promising. In this article, we propose a hybrid Meta-Heuristic based approach for complex scheduling with several manufacturing and assembly operations, in dynamic Extended Job-Shop environments. Some self-adaptation mechanisms are proposed.

Related Content

Syeda Mariam Muzammal, Ruqia Bibi, Hira Waseem, Syed Nizam Ud Din, N. Z. Jhanjhi, Muhammad Tayyab. © 2025. 28 pages.
Siva Raja Sindiramutty, N. Z. Jhanjhi, Rehan Akbar, Tariq Rahim Soomro, Mustansar Ali Ghazanfar. © 2025. 54 pages.
Khizar Hameed, Muhammad Tayyab, Noor Zaman Jhanjhi, Syeda Mariam Muzammal, Majid Mumtaz. © 2025. 54 pages.
Kritika. © 2025. 32 pages.
Qurat-ul Ain Zam Zam, Humaira Ashraf, N. Z. Jhanjhi, Atta Ullah, Fathi Amsaad. © 2025. 22 pages.
Siva Raja Sindiramutty, Krishna Raj V. Prabagaran, N. Z. Jhanjhi, Raja Kumar Murugesan, Sarfraz Nawaz Brohi, Goh Wei Wei. © 2025. 44 pages.
Siva Raja Sindiramutty, N. Z. Jhanjhi, Rehan Akbar, Manzoor Hussain, Sayan Kumar Ray, Fathi Amsaad. © 2025. 52 pages.
Body Bottom