Multi-Agent Based Beam Search for Real-Time Production Scheduling and Control
Author | : Shu Gang Kang |
Publisher | : Springer Science & Business Media |
Total Pages | : 136 |
Release | : 2012-10-11 |
ISBN-10 | : 9781447145752 |
ISBN-13 | : 1447145755 |
Rating | : 4/5 (52 Downloads) |
Download or read book Multi-Agent Based Beam Search for Real-Time Production Scheduling and Control written by Shu Gang Kang and published by Springer Science & Business Media. This book was released on 2012-10-11 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Multi-Agent Based Beam Search (MABBS) method systematically integrates four major requirements of manufacturing production - representation capability, solution quality, computation efficiency, and implementation difficulty - within a unified framework to deal with the many challenges of complex real-world production planning and scheduling problems. Multi-agent Based Beam Search for Real-time Production Scheduling and Control introduces this method, together with its software implementation and industrial applications. This book connects academic research with industrial practice, and develops a practical solution to production planning and scheduling problems. To simplify implementation, a reusable software platform is developed to build the MABBS method into a generic computation engine. This engine is integrated with a script language, called the Embedded Extensible Application Script Language (EXASL), to provide a flexible and straightforward approach to representing complex real-world problems. Adopting an in-depth yet engaging and clear approach, and avoiding confusing or complicated mathematics and formulas, this book presents simple heuristics and a user-friendly software platform for system modelling. The supporting industrial case studies provide key information for students, lecturers, and industry practitioners alike. Multi-agent Based Beam Search for Real-time Production Scheduling and Control offers insights into the complex nature of and a practical total solution to production planning and scheduling, and inspires further research and practice in this promising research area.