An agent-based modeling framework for the design of a dynamic closed-loop supply chain network


Bozdoğan A., Görkemli Aykut L., Demirel N.

COMPLEX & INTELLIGENT SYSTEMS, 2022 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Publication Date: 2022
  • Doi Number: 10.1007/s40747-022-00780-z
  • Journal Name: COMPLEX & INTELLIGENT SYSTEMS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), INSPEC
  • Keywords: Closed-loop supply chain (CLSC), Network design, Agent-based modeling (ABM), Customer behavior, AnyLogic, OPTIMIZATION MODEL, REVERSE LOGISTICS, PRODUCT-RECOVERY, SIMULATION, UNCERTAINTY, DEMAND, HYBRID, NEGOTIATION, INTEGRATION, MANAGEMENT
  • Erciyes University Affiliated: Yes

Abstract

The 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.