Self-optimization for dynamic scheduling in manufacturing systems


Autoria(s): Madureira, Ana Maria; Pereira, Ivo
Data(s)

15/04/2013

15/04/2013

2010

11/04/2013

Resumo

Scheduling is a critical function that is present throughout many industries and applications. A great need exists for developing scheduling approaches that can be applied to a number of different scheduling problems with significant impact on performance of business organizations. A challenge is emerging in the design of scheduling support systems for manufacturing environments where dynamic adaptation and optimization become increasingly important. In this paper, we describe a Self-Optimizing Mechanism for Scheduling System through Nature Inspired Optimization Techniques (NIT).

Identificador

DOI 10.1007/978-90-481-9151-2_74

978-90-481-9150-5

978-90-481-9151-2

http://hdl.handle.net/10400.22/1270

Idioma(s)

eng

Publicador

Springer Netherlands

Relação

Technological Developments in Networking, Education and Automation;

http://link.springer.com/chapter/10.1007/978-90-481-9151-2_74

Direitos

closedAccess

Palavras-Chave #Self-optimization #Multi-agent learning #Autonomic computing #Multi-agent systems #Nature inspired optimization techniques
Tipo

bookPart