Abstract
With the development of lean manufacturing and economic globalization, supply networks increasingly become complex and large-scale, within which thousands of firms inter-depend with each other. Due to these increasing inter-dependencies, disruption of a quite few critical suppliers, namely bottleneck suppliers, can induce high loss to a supply network and even make the whole network dysfunction. Identification of bottleneck suppliers is significantly important for supply network risk management. Thus, in this article, a method based on a memetic algorithm with local neighborhood search (MALNS) is proposed to identify bottleneck suppliers in a two-stage supply network. Firstly, a model based on multipartite network is designed to describe the product supply-demand relations between multiple manufacturers and suppliers, which considers the different roles of manufacturer and supplier and differentiates the products that suppliers supply. To assess the loss caused by supplier disruptions, two performance metrics of supply networks, average product availability rate and manufacturer functioning rate, are presented. Then, a MALNS-based method is proposed to identify bottleneck suppliers, i.e., suppliers whose disruption will decrease both performance metrics most greatly. Finally, a case study based on a real automobile supply network is presented to validate the applicability and effectiveness of the proposed method.
Highlights
Networks are constructed when manufacturers rely on suppliers to purchase products in order to accomplish the final products [1]
Considering the out performance of Memetic algorithm (MA) in many other fields, this study proposes a MA improved by a local neighborhood searching procedure, which is named as memetic algorithm with local neighborhood search (MALNS), to identify the bottleneck suppliers
The proposed local neighborhood search procedure can effectively increase the performance of MA, suggesting that MALNS is a suitable method for detecting bottleneck suppliers
Summary
Networks are constructed when manufacturers rely on suppliers to purchase products in order to accomplish the final products [1]. The model without differentiating the products that suppliers supplying will not reflect the importance of suppliers supplying rare products, disruption of such suppliers would halt the production of manufacturers These previous works proposed a lot of complex network-based supply network models and corresponding performance metrics. Common used network centrality measures, such as degree centrality and betweenness centrality are discussed in the context of supply networks Based on these centrality metrics, they propose a methodology for identifying bottleneck suppliers, i.e., suppliers that can induce high losses owing to disruptions in a supply network. These network centrality metrics can only provide an approximation on how vital a supplier is to the performance of a supply network Most of these studies are from theoretic point of view or are limited by using simple and theoretical supply network model to validate their methods. Edges only exist between nodes in M and P and between nodes in P and S
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