A novel supply-demand matching model for shared manufacturing resources

匹配(统计) 业务 供求关系 供应链 计算机科学 产业组织 经济 微观经济学 营销 统计 数学
作者
Yunzhi Cheng,Chunxia Yu,Suxiu Xu,Shaoqiong Zhao
出处
期刊:International Journal of Computer Integrated Manufacturing [Taylor & Francis]
卷期号:: 1-25
标识
DOI:10.1080/0951192x.2024.2426152
摘要

Shared manufacturing is an innovative application of the sharing economy in manufacturing field, aiming to optimize capacity utilization and improve the efficiency of supply-demand matching. The supply-demand matching of manufacturing resources is a key issue on the shared manufacturing platform. In practice, shared manufacturing is proposed based on the objective of optimizing capacity utilization of idle manufacturing resources. In addition, multi-attributes on manufacturing resources are negotiated simultaneously, such as price, quality, and delivery time. However, the existing supply-demand matching models neither consider the optimization objective of capacity utilization nor multi-attribute negotiation requirements. The objective of this research is to propose a novel supply-demand matching model for the shared manufacturing resources, including a double auction-based supply-demand matching relationship determination and a multi-attribute negotiation-based transaction detail determination. In the first stage, a double auction model of manufacturing resources is proposed to determine the matching relationship between provider and demanders. In the proposed double auction model, utility functions for both parties are constructed to express their personalized preferences on bidding attributes; bidding strategies for both parties are determined to generate bidding values; a winner determination model is proposed to determine the matched provider and demander of manufacturing resources maximizing social welfare and capacity utilization. In the second stage, a multi-attribute negotiation model is developed to determine the concrete deal information of manufacturing resources, such as transaction prices, quality, and delivery time. Finally, the feasibility and efficiency of the proposed model is verified through numerical examples.
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