A reconfigurable manufacturing system (RMS) is a type of manufacturing system that is meant to be extremely adaptable to changing production requirements. Unlike traditional manufacturing systems, which are often dedicated to a specific product or production process, RMS can be quickly reconfigured to accommodate new products, production processes, or changes in production demand. Based on the interconnections between different modules and the capabilities of the machines, the current study presents a technique for assessing the machine usage utilization, reconfigurability, and operating capability of a Reconfigurable machine tool (RMT). The performance parameters and costs are considered as several objectives for optimizing machine assignment. In this work, multi-objective optimization of RMS was performed in two stages. NSGAII is used in the first stage to generate non-dominated solutions. The Pareto frontiers are ranked using a multiple-attribute decision-making approach in the second stage. To rank the provided solutions, the TOPSIS algorithm and entropy theory were employed. According to the outcomes, the combination of the proposed performance indicators and the hybrid technique has great potential for dealing with optimization and cost–benefit concerns in RMS.