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Multi-Agent Based Beam Search for Real-Time Production Scheduling and Control

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Produktnummer: 188c430f296a1445f89771dd1b66df951f
Autor: Choi, Shiu Hong Kang, Shu Gang
Themengebiete: Beam Search Decision Making Engineering Economics Knowledge Representation Multi-agent Systems Production Planning
Veröffentlichungsdatum: 11.11.2014
EAN: 9781447161653
Sprache: Englisch
Seitenzahl: 134
Produktart: Kartoniert / Broschiert
Verlag: Springer London
Untertitel: Method, Software and Industrial Application
Produktinformationen "Multi-Agent Based Beam Search for Real-Time Production Scheduling and Control"
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.
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