Flexible manufacturing systems: a review of analytical models
Management Science
Task differentiation in Polistes wasp colonies: a model for self-organizing groups of robots
Proceedings of the first international conference on simulation of adaptive behavior on From animals to animats
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Artificial Life
Future Generation Computer Systems
Adaptive Task Allocation Inspired by a Model of Division of Labor in Social Insects
Biocomputing and emergent computation: Proceedings of BCEC97
Wasp-like Agents for Distributed Factory Coordination
Autonomous Agents and Multi-Agent Systems
The Contract Net Protocol: High-Level Communication and Control in a Distributed Problem Solver
IEEE Transactions on Computers
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This article presents a self-adaptive, wasp-based control model for real-time part routing in a flexible manufacturing system (FMS). Inspired from the natural system of a wasp colony, the proposed control model is a multi-agent system that exhibits adaptive behaviour. It uses simple rules built on a decentralized architecture and hence it overcomes the drawbacks of traditional agent-based systems, such as long negotiation times among agents. The production problem, which has been previously studied in the literature, includes real-time routing of parts with the objective of minimizing average waiting times and average cycle times in a large FMS that consists of 40 machines. The proposed wasp-based control model is benchmarked via simulation under various experimental conditions against those previously published studies. The simulation study shows that it outperforms the previously reported studies when the production system is heavily loaded and prone to congestion. The self-adaptive nature of the proposed model makes it robust in the presence of such dynamic, unexpected changes occurring in the FMS.