A PSO and Simulated Annealing Hybrid Algorithm to Task Allocation Problem for Holonic Manufacturing System

This paper focuses on the dynamic reconfiguration and task optimization of holonic manufacturing systems (HMS). The concept of dynamic virtual clustering is extended to the control process of a holarchy or holonic organization. The mediator-based dynamic virtual clustering mechanism is presented firstly. Then a negotiation strategy based on the contract net protocol is proposed for cooperative action among holons. Finally, a hybrid algorithm based on PSO and simulated annealing for holon task allocation is described to support the optimum organization of a holarchy. PSO employs a collaborative population-based search, which is inspired by the social behavior of bird flocking. It combines local search (by self experience) and global search (by neighboring experience), possessing high search efficiency. SA employs certain probability to avoid becoming trapped in a local optimum and the search process can be controlled by the cooling schedule. The hybrid algorithm combines the high speed of PSO with the powerful ability to avoid being trapped in local minimum of SA. We compare the PSO algorithm to both GA and SA models, the simulation results show that the proposed model and algorithm are effective