This paper presents a multiagent modeling framework for supply chain dynamics, designed to overcome the challenges of developing detailed and reusable models. The framework is based on a library of software components representing different types of supply chain agents (e.g., retailers, manufacturers, transporters) and their control elements (e.g., inventory policies, interaction protocols). The authors describe the framework's architecture, which includes structural and control elements, and demonstrate its application through a cross-docking prototype in the grocery industry. The framework aims to facilitate rapid development of customized decision support tools for supply chain management, enabling detailed risk-benefit analysis and performance evaluation under various scenarios. The paper also reviews existing research and approaches, highlighting the need for a flexible and reusable framework to handle the complexity of supply chain dynamics.This paper presents a multiagent modeling framework for supply chain dynamics, designed to overcome the challenges of developing detailed and reusable models. The framework is based on a library of software components representing different types of supply chain agents (e.g., retailers, manufacturers, transporters) and their control elements (e.g., inventory policies, interaction protocols). The authors describe the framework's architecture, which includes structural and control elements, and demonstrate its application through a cross-docking prototype in the grocery industry. The framework aims to facilitate rapid development of customized decision support tools for supply chain management, enabling detailed risk-benefit analysis and performance evaluation under various scenarios. The paper also reviews existing research and approaches, highlighting the need for a flexible and reusable framework to handle the complexity of supply chain dynamics.