This paper presents a novel approach for supply chain management that is based on two elements: a framework for dynamically modeled decentralized supply chains and the design of systematic decision-making processes for improving the performance of supply chains. This framework captures the dynamic behavior of supply chains by modeling the flow of materials and information within the supply chain. It also considers supply chains as decentralized systems where there is no global coordinator and every node in the system makes decisions locally. Regarding the decision-making processes, this approach assumes that the decisions can be seen as the control or manipulated variables of a dynamic system, and as such a control law defines them. The aim of the study is to analyze the impact of different heuristic control laws on the performance of supply chains integrated by multiproduct, multistage distribution networks and manufacturing sites with single-unit, multiproduct, nondedicated batch or continuous processes. The study applies several control laws to the model and compares their performance in terms of operational costs, ability to maintain a high customer satisfaction level, and stability of inventories. The results provide information about the tradeoffs found in real systems and give valuable insights for future work on the control of supply chains.