###### Abstract
Furthermore, because of its short life cycle, which causes variations in product mix and demand over time, it is more realistic to focus on dynamic rather than static situations in the manufacturing system. These days, dynamic CMS has drawn the attention of a majority of researchers, since it is more realistic and useful. The issues of Cellular Manufacturing Systems and dynamic environments have attracted significant attention from researchers in recent times [5]. Reduced movement of parts, throughput time, customer order response time, and work-in-process (WIP) are a few of the benefits of cellular manufacturing. All of these reductions contribute to a rise in profitability. The reduction in response time to customer orders enables businesses to respond swiftly to alterations in customer requirements and, as a result, to maintain a competitive advantage despite the rapid evolution of market demands. The parts in a Cellular Manufacturing System are grouped according to common characteristics such as shape, tolerance, and process plan. We refer to these sets of components as part families. In CMS, there are numerous machine cells, and within each machine cell are various machines devoted to producing one or more part families. By cutting down on setup, wait, and move times, the CMS installation shortens throughput times. It also  
Figure 1: Cellular layout. lowers material handling costs and inventory levels while speeding up market reaction times [6]. The sequencing of the machines in each cell or group and the IDs of part families are all part of the Cellular Manufacturing System (CMS) implementation process. Cell creation is the grouping of machines into cells on the shop floor [7]. Grouping machines (Cell Formation) is a crucial step in the design of a Cellular Manufacturing System [8]. Parts that share the same manufacturing needs are now organized into part families and assigned to distinct pieces of machinery for processing. In the realm of cellular manufacturing, the generation of cells or groups of machines is a thoroughly researched problem with a wealth of reviews and taxonomies available [9; 10], but the layout delinquent in CMS has rarely captivated researchers' attention as much as Cell Formation (grouping of machines) [11]. The objective of facility layout is to arrange a collection of facilities so as to minimize the qualitative (information flow, noise disturbance, and work between parts) or quantitative (material handling cost, product manufacturing cost, scheduling cost, etc.) objective functions on the shop floor [12]. Material handling is considered the most time-intensive objective function in manufacturing system layout design. The objective of CMS facility layout problems is to determine the arrangement of facilities in machine cells and the shop floor layout of cells. The primary objective of this paper is to optimally position machines within the cell. Genetic Algorithms (GAs) with machine encoding schemes have been proposed for this purpose. The remainder of this paper is organized as follows. In Section 2, the literature review is presented. The Genetic Algorithm and mathematical model are, respectively, illustrated in Sections 3 and 4. The analysis of results is discussed in Section 5. Finally, the paper concludes with Section 6.