Advisor(s)
Abstract(s)
Manufacturing activities and production control are constantly growing.
Despite this, it is necessary to improve the increasing variety of scheduling
and layout adjustments for dynamic and flexible responses in volatile
environments with disruptions or failures. Faced with the lack of realistic
and practical manufacturing scenarios, this approach allows simulating
and solving the problem of job shop scheduling on a production system by
taking advantage of genetic algorithm and particle swarm optimization
algorithm combined with the flexibility and robustness of a multi-agent
system and dynamic rescheduling alternatives. Therefore, this hybrid
decision support system intends to obtain optimized solutions and enable
humans to interact with the system to properly adjust priorities or refine
setups or solutions, in an interactive and user-friendly way. The system
allows to evaluate the optimization performance of each one of the
algorithms proposed, as well as to obtain decentralization in
responsiveness and dynamic decisions for rescheduling due to the
occurance of unexpected events.
Description
Keywords
Human-centred Industry 4.0 Metaheuristics Multi-agent system Optimization Scheduling
Citation
Alves, Filipe; Varela, Maria Leonilde R.; Rocha, Ana Maria A.C.; Pereira, Ana I.; Leitão, Paulo (2019). A human centred hybrid MAS and meta-heuristics based system for simultaneously supporting scheduling and plant layout adjustment. FME Transactions. ISSN 1451-2092. 47, p. 699-710