Abstract
A distributed decision making system for integrated optimization of production scheduling and distribution planning is proposed. The system consists of several subsystems that individually derive the solution of its own subproblem to minimize the objective function obtained by decomposing the problem using an augmented Lagrangian decomposition and coordination technique. The proposed approach is applied to planning and scheduling for an aluminum rolling processing line. Decision variables such as arrival date of raw materials, lot-sizing, production scheduling, and allocation of products to warehouses are optimized simultaneously by repeating local optimization in material resource planning, and scheduling subsystem for each production process and warehouse planning subsystem. The effectiveness of the proposed approach is demonstrated.
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