ORIGINAL ARTICLE Machine–part cell formation using a hybrid particle swarm optimization Mona Anvari & Mohammad Saidi Mehrabad & Farnaz Barzinpour Received: 23 November 2008 / Accepted: 8 July 2009 / Published online: 22 July 2009 # Springer-Verlag London Limited 2009 Abstract Cell formation (CF) is a key step in group technology (GT). This combinatorial optimization problem is NP-complete. So, meta-heuristic algorithms have been extensively adopted to efficiently solve the CF problem. Particle swarm optimization (PSO) is a modern evolution- ary computation technique based on a population mecha- nism. Since Kennedy and Eberhart invented the PSO, the challenge has been to employ the algorithm to different problem areas other than those that the inventors originally focused on. This paper investigates the first applications of this emerging novel optimization algorithm into the CF problem, and a newly developed PSO-based optimization algorithm for it is elaborated. Forming manufacturing cells lead to process each part family within a machine group with reduction intracellular travel of parts and setup time. A maximum number of machines in a cell and the maximum number of cells are imposed. Some published results in various problem sizes have been used as benchmarks to assess the proposed algorithm. Overall, the advantages of the proposed PSO are that it is rapidly converging towards an optimum, there are fewer parameters to adjust, it is simple to compute, it is easy to implement, it is free from the complex computation, and it is very efficient to use in CF with a wide variety of machine/part matrices. Keywords Cellular manufacturing . Part–machine grouping problem . Particle swarm optimization 1 Introduction The production process requires a variety of machines and often some complex procedures. Frequently, parts have to be moved from one place to another. This not only results in machine idle time but also wastes the manpower required for the physical movement of the parts. On the other hand, an increasing number of companies are encountering small- to medium-size production orders. In this situation, more setup changes and frequent part or machine movements occur [3]. Group technology (GT) is a manufacturing philosophy that has proven to be a useful way of addressing these problems, and so, it has attracted a lot of attention because of its positive impacts in productivity and flexibility of the batch-type production. It can be used to exploit similarities between components to achieve lower costs and increase productivity without losing product quality. Cellular man- ufacturing (CM) is an application of GT principles to design manufacturing systems. A number of benefits arise from adopting CM, such as reduced inventory, reduced capacity, reduced labor and overtime costs, shorter manufacturing lead times, faster response to internal and external changes such as machine failures, product mix, and demand changes [4]. Information such as parts to be produced, process plans, and machines to perform all the required operations is needed when designing CM. Machines are then assigned to these cells to process one or more part families so that each cell is operated independently and so that the intercellular move- ments are minimized or the number of part flow processed within cells is maximized, i.e., parts do not have to move from one cell to the other for processing [5]. In the design of a CM system, similar parts are grouped into families based on common processing requirements M. Anvari (*) : M. S. Mehrabad : F. Barzinpour Department of Industrial Engineering, Iran University of Science and Technology, Narmak, 16844 Tehran, Iran e-mail: manvari@iust.ac.ir M. S. Mehrabad e-mail: mehrabad@iust.ac.ir Int J Adv Manuf Technol (2010) 47:745–754 DOI 10.1007/s00170-009-2202-9