反應規模經濟與需求波動之供應鏈網路設計

Abstract

The extremely complexity of designing a supply chain network is due to the need for the configuration to adhere to customer demands, and manufacturer’s capacity and production must treat demand fluctuations. In supply chain network design phases, manufacturers merely use average estimated demand patterns, where peak and off-peak periods are covered. However, the uncertainty surrounding input parameters complicates the network design. A flexible supply chain network design that could better respond to demand fluctuations is more appropriate for operational planning. Regarding delivery strategies, the goal is to reduce logistics costs and satisfy customer needs. The assumption of constant demand is highly controversial, since demand varies with time, space and consumer socioeconomic characteristics. Serving all customers without considering the above causes high logistics cost and low customer satisfaction, thus a reduced profit. This study aims to investigate the supply chain network design problems in response to economies of scale and demand fluctuations. A series of models are formulated to systematically investigate the problems and analyze manufacturers’ decisions on how much and how often material/product to purchase/transport among/to suppliers/customers as well as the optimal capacity and production amount for multiple plants with economies of scale in an uncertain environment. According to the issues of significance, the dissertation is divided into five distinct parts. The first part formulates an integrated plant capacity and production model, which aims to investigate how economies of scale, customer demand levels and investment conditions in different locations influence the supply chain network design. The second part focuses on evaluating the reliability of the network design from the first part on condition that abnormal demand fluctuations occur. Two mathematical programming models are further developed to determine the optimal adjustment decisions regarding production reallocation among plant under different fluctuating demand. In the third part, the network design model is extended to include the inbound and outbound dispatching decisions with shipping economies in the supply chain. Then, the network is narrowed down to two echelons, such as plants and customers in the forth part, to focus on the logistics issues in the supply chain network. The demand-supply interaction models, which optimize a delivery service strategy, are developed as they cope with time and spatial dependent demand, demand-supply interaction. Moreover, the impacts of demand-supply interaction on the optimal capacity and production allocation among the manufacturing plants are also investigated. Furthermore, in the fifth part of the dissertation, this study focuses on the end consumer shopping behavior and employs Internet shopping as the study object. The impacts of consumer characteristics on the optimal delivery service problems are emphasized. Specifically, in addition to the determination of the optimal number and duration of service cycles by exploring demand-supply interaction and time-dependent consumer demand, this part also investigates how variations in consumer socioeconomic, temporal and spatial distributions influence consumer demand and, thereby, profit. A series of case studies are performed to demonstrate the applications of the study. The results show the benefits in terms of cost savings brought by centralized production are larger than the increased transportation cost as a result of decentralization. The results also show performing an adjustment in response to demand expansion benefits the manufacturer in way that total production cost is reduced and revenue loss is avoided, which outweigh the additional costs. The results also show the total monthly material/product flows between two locations impacts more than their distance does on the optimal shipping frequency. The results also imply for two locations that are distant apart; there must be a large economical shipment size or less frequent shipment. The results show that without considering demand-supply interaction, the manufacturer typically pursues minimized logistics cost by assuming inelastic customer demand and applying less delivery service cycles. However, this strategy overestimates customer demand and yields higher production cost, leading to a reduced profit. In sum, the results of the study provide a reference for the manufacturer in the decision making procedures of network planning with economies of scale and demand fluctuations, as they cope with related benefits and costs.