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Capacity planning deals with the conflicts among multiple factories. This study employs a negotiation framework to allow autonomous budget allocation among factories and make full use of manufacturing resources capacity scattered over individual factories. Factories are modeled as intelligent entities that exchange offer messages with one another. This study investigates the effects of the attitudes of a factory, while it bargains with other factories over the budget. Furthermore, individual factories apply a capacity-planning optimization model and a genetic algorithm to revise their capacity plan right after receiving new messages from other factories. This paper makes a contribution in successfully building a negotiation-based capacity-planning model applied to a multiple-factory environment. The outcome of the experiments shows the efficiency of the proposed model and the effect of different negotiation attitudes.