Cell Formation (CF) and Group Layout (GL) are two important problems in designing a cellular manufacturing system. This article addresses an integrated CF and GL model as a mixed-integer program, considering energy consumption, assembly aspects and process routing. As a novel feature, machines are assumed to be capable of processing operations with different energy consumption rates and processing times. This model aims to determine concurrently machine cells, the layout of facilities (machines, workstations and cells), process routes and processing speed of operations so that the materials handling cost and the electric energy consumption are minimized. To demonstrate the applicability of the model, managerial insights are provided by a case study. Owing to the computational complexity of the problem, a hybrid solution approach combining a Genetic Algorithm (GA) and Simulated Annealing (SA) is proposed. The computational results demonstrate the superiority of the hybrid approach over CPLEX${}^{\circledR }$ and conventional GAs and SA.

单元形成 (CF) 和组布局 (GL) 是设计单元制造系统时的两个重要问题。本文将集成的 CF 和 GL 模型作为一个混合整数程序，考虑到能源消耗、装配方面和工艺路线。作为一项新功能，假设机器能够处理具有不同能耗率和处理时间的操作。该模型旨在同时确定机器单元、设施（机器、工作站和单元）的布局、工艺路线和操作的处理速度，从而最大限度地降低物料搬运成本和电能消耗。为了证明模型的适用性，案例研究提供了管理见解。由于问题的计算复杂性，提出了一种结合遗传算法（GA）和模拟退火（SA）的混合求解方法。计算结果证明了混合方法优于 CPLEX${}^{\circledR }$和传统的 GA 和 SA。