关键词: 多品牌服装企业, 产能规划, 订单分配, 两阶段随机鲁棒, Benders分解

Abstract:

Objective After moving away from low-priced labeling, Chinese garment enterprises have entered the era of building their own brands and carrying out multi-brand strategy. Because of the distinct development history and positioning of each brand, most enterprises operate their multi-brand in a decentralized way, i.e., each brand division has its own supplier base. This ensures the independence and competitiveness of each brand, but leads to the loss of opportunities to integrate these supplier bases. To this end, this paper considers the multi-brand garment enterprises and studies the integrated optimization of supplier selection, capacity planning, and order allocation.

Method Considering decision-makers faced the demand uncertainties, and multiple requirements on demand satisfaction, cost, and operations, a two-stage stochastically robust model was developed. The first stage focused on the supplier selection and capacity planning decisions, which should be made before demand information was given. Next, the order would be assigned to the selected supplier. Orders consisted of two parts, the first being the allocated order quantity that was consistent with the capacity planning characteristics, and the other being the adjusted order quantity obtained by integrating the unused planned capacity of suppliers. A solution method based on Benders decomposition was designed to improve the computational efficiency.

Results The proposed approach was applied to address a real-world case of a well-known multi-brand garment enterprise in China. Sensitivity analysis for the mismatch degree and the robustness-economics weighted value was also conducted. First of all, by comparing whether to implement the capacity sharing decision among brands, it was found that capacity sharing could effectively reduce the loss of unfulfilled orders and make the total cost better. The differences in supplier production capacity and order demand led to different trends in order adjustments for various brand suppliers as market demand increased. To be specific, in an event that market demand for all brands was rising, the less-demanding brand would arrange for its own suppliers to dedicate more capacity to producing orders for other brands with higher demand. However, demanding requirement on the match of the planning and the operational results seemed beneficial to stabilize the operations of suppliers, it also resulted in two disadvantages: harm to the benefits of the garment enterprises and reduction in the capacity utilization of the suppliers. Especially when the threshold of capacity planning matching degree was above 0.4, the out-of-stock cost as well as the total cost of the enterprise got significantly increased. A trade-off existed between the robustness and the economics of the decision-making results. Correspondingly, the economic requirement could be improved at the price of the robustness, and vice versa. With the increase of model robustness requirement, the total order shortage was decreased and the supplier's order adjustment was increased. This also indicated that the order adjustment strategy could effectively alleviate the imbalance between supply and demand.

Conclusion This paper highlights the importance of supplier resource coordination between brands. Specifically, the implementation of capacity sharing and order adjustment strategies can effectively improve the supply and demand balance of manufacturing resources and uncertain market demand. Both high-demand and low-demand brand divisions have the incentive to share supplier capacity. The high-demand division prefers capacity sharing because much capacity can be obtained via this practice, while the low-demand division will benefit from the capacity sharing by increasing the capacity utilization of its supplier bases. In addition, this paper comprehensively considers the trade-offs between cost, market, and supplier relationships in the modeling process. Therefore, it provides the scientific basis for supplier management of multi-brand garment enterprises, and the decision-making support for the win-win of garment enterprises and their suppliers.

Key words: multi-brand garment enterprises, capacity planning, order allocation, two-stage stochastically robust, Benders decomposition