Abstract
AbstractThe supply chain is a dynamic and uncertain system consisting of material, information, and fund flows between different organizations, from the acquisition of the raw materials to the delivery of the finished products to the end customers. Closed-loop supply chains do not end with the delivery of the finished products to the end customers, the process continues until economic value is obtained from the returned products or they are disposed properly in landfills. Incorporating reverse flows in supply chains increases the uncertainty and complexity, as well as complicating the management of supply chains that are already composed of different actors and have a dynamic structure. Since agent-based modeling and simulation is a more efficient method of handling the dynamic and complex nature of supply chains than the traditional analytical methods, in this study agent-based modeling methodology has been used to model a generic closed-loop supply chain network design problem with the aims of integrating customer behavior into the network, coping with the dynamism, and obtaining a more realistic structure by eliminating the required assumptions for solving the model with analytical methods. The actors in the CLSC network have been defined as agents with goals, properties and behaviors. In the proposed model dynamic customer arrivals, the changing aspects of customers' purchasing preferences for new and refurbished products and the time, quantity and quality uncertainties of returns have been handled via the proposed agent-based architecture. To observe the behavior of the supply chain in several conditions various scenarios have been developed according to different parameter settings for the supplier capacities, the rate of customers being affected by advertising, the market incentive threshold values, and the environmental awareness of customers. From the scenarios, it has been concluded that the system should be fed in the right amounts for the new and refurbished products to increase the effectiveness of factors such as advertising, incentives, and environmental awareness for achieving the desired sales amounts and cost targets.
Funder
Erciyes University Scientific Research Projects Coordination Unit
Publisher
Springer Science and Business Media LLC
Subject
Computational Mathematics,Engineering (miscellaneous),Information Systems,Artificial Intelligence
Reference118 articles.
1. Abdi A, Abdi A, Fathollahi-Fard H-KM (2021) A set of calibrated metaheuristics to address a closed-loop supply chain network design problem under uncertainty. Int J Syst Sci Oper Logist 8(1):23–40
2. Achmad ALK, Chaerani HD, Perdana T (2021) Designing a food supply chain strategy during COVID-19 pandemic using an integrated agent-based modelling and robust optimization. Heliyon 7(11)
3. Afshari H, McLeod R, El Mekkawy T, Peng O (2014) Distribution-service network design: an agent-based approach, pp. 651–656. In: Variety Management in Manufacturing. Proceedings of the 47th CIRP Conference on Manufacturing Systems, 28–30, Windsor
4. Ahn HJ, Lee H (2004) An agent-based dynamic information network for supply chain management. BT Technol J 22(2):18–27
5. Akanle OM, Zhang DZ (2008) Agent based model for optimising supply chain configuration. Int J Prod Econ 115:444–460
Cited by
6 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献