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Pheromone based emergent shop floor control system for flexible flow shops

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TLDR
A development approach for agent-based shop floor control systems is presented, that uses co-ordination concepts as observable in insect colonies to introduce better response to unanticipated disturbance situations and better handling of ‘reconfiguration’ in production environments.
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The article was published on 1999-12-01 and is currently open access. It has received 74 citations till now.

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Citations
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Auto ID systems and intelligent manufacturing control

TL;DR: The way in which both conventional control methods and so-called distributed, intelligent control methods can be enhanced by the availability of accurate, timely information about an item is examined.
Journal ArticleDOI

Ant colony intelligence in multi-agent dynamic manufacturing scheduling

TL;DR: Simulation results show that, for most of the performance measures, a MAS integrated with well-designed ant-inspired coordination performs well compared to a MAS using dispatching rules.
Journal ArticleDOI

Emergent synthesis methodologies for manufacturing

TL;DR: This paper offers a concise overview of new manufacturing methodologies that are based on emergent synthesis by reviewing about 300 papers according to the problem classification and in terms of three phases of concept formation, theory and application.
Journal ArticleDOI

Dynamic flexible job shop scheduling with alternative process plans: an agent-based approach

TL;DR: In this paper, a pheromone-based approach is proposed for coordination among agents in a flexible job shop problem considering dynamic events such as stochastic job arrivals, uncertain processing times, and unexpected machine breakdowns.
Journal ArticleDOI

Autonomous control of production networks using a pheromone approach

TL;DR: To manage dynamic networks according to low work-in-progress and short throughput times, an autonomous control approach is proposed that means a decentralized routing of the autonomous parts themselves.
References
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Journal ArticleDOI

Ant system: optimization by a colony of cooperating agents

TL;DR: It is shown how the ant system (AS) can be applied to other optimization problems like the asymmetric traveling salesman, the quadratic assignment and the job-shop scheduling, and the salient characteristics-global data structure revision, distributed communication and probabilistic transitions of the AS.
Book

Multiagent Systems : A Modern Approach to Distributed Artificial Intelligence

TL;DR: This is the first comprehensive introduction to multiagent systems and contemporary distributed artificial intelligence and will be a useful reference not only for computer scientists and engineers, but for social scientists and management and organization scientists as well.
Book

The ant colony optimization meta-heuristic

TL;DR: This chapter contains sections titled: Combinatorial Optimization, The ACO Metaheuristic, How Do I Apply ACO?
Journal ArticleDOI

AntNet: distributed stigmergetic control for communications networks

TL;DR: AntNet is a distributed, mobile agents based Monte Carlo system that was inspired by recent work on the ant colony metaphor for solving optimization problems, and showed superior performance under all the experimental conditions with respect to its competitors.
Book

New Ideas In Optimization

TL;DR: The techniques treated in this text represent research as elucidated by the leaders in the field and are applied to real problems, such as hilllclimbing, simulated annealing, and tabu search.