| Summary: | 碩士 === 元智大學 === 工業工程與管理學系 === 94 === Global production becomes the trend for firms to compete in conforms of customer’s quick response requirement. Nowadays, a firm would accept orders from all customers and assign the orders to a proper plant for manufacturing goods based on the setup cost, manufacturing cost, inventory holding cost, and the capacity constraint at different plants. The transportation cost that is seldom considered may cause a higher total supply chain cost for fulfilling an order. Thus, order allocation for multi-plant multi-item multi-period based on the total system cost is discussed in this research.
In this research we first formulate the problem based on one item problem. The objective is to minimize the total system cost that takes into account the setup cost, manufacturing cost, inventory holding cost, and the transportation cost for deliver the items to the order’s destination. Then extend the problem into multi-item production problem. Lagrangian-based approach is a popular approach to solve many practical optimization problems. Thus, we propose a Lagrangian relaxation-based algorithm that relaxes the capacity constraint, while Lagrangian multipliers are updated by using a subgradient method. At each iteration, a feasible solution of the original problem is constructed from the solution of the relaxed problem with an order shifting and backwarding approach.
About 12 randomly generated instances of the single-item and multi-item problem have been solved, respectively. The same instances are also solved by LINGO. It has been found that Lagrangian heuristic works quite “efficiently” for this problem. The results of sensitivity analysis in different parameters show that the manufacturing cost and transportation cost are two most important factors to be considered for multi-plant multi-item multi-period order allocation problem.
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