Decentralized capacity allocation of a single-facility with fuzzy demand

• The decentralized capacity allocation problem in a fuzzy environment is investigated for the first time.
• Private information and uncertainties are taken into account simultaneously.
• Based on mathematical method and fuzzy theory, an interactive procedure is proposed to solve the formulated capacity allocation problem.

Capacity allocation under uncertainty environment is an important decision problem in manufacturing. The decentralized capacity allocation of a single-facility among different organizations with fuzzy demand is investigated in this paper. The objective and demand of each organization are assumed to be private information that other organizations and the facility cannot access to. In addition, we assume organizations have limited view of the capacity and loading of the facility. First, fuzzy optimization models associated with each organization and the facility are set up. Then, based on fuzzy theory, the fuzzy optimization models are converted into parametric programming models and subsequently an interactive algorithm is proposed to solve those parametric programming models. The extra benefit of this algorithm is that the whole solving process is amenable to decentralized implementation. Finally, experimental results illustrate the effectiveness of this work under two levels of information sharing: capacity information of the facility unknown to organizations and capacity information of the facility partially known to organizations.