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Manufacturing Cell Design: An Integer Programming Model Employing Genetic Algorithms
 IIE Transactions
, 1996
"... The design of a cellular manufacturing system requires that a part population, at least minimally described by its use of process technology (part/machine incidence matrix), be partitioned into part families and that the associated plant equipment be partitioned into machine cells. At the highest le ..."
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Cited by 15 (5 self)
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The design of a cellular manufacturing system requires that a part population, at least minimally described by its use of process technology (part/machine incidence matrix), be partitioned into part families and that the associated plant equipment be partitioned into machine cells. At the highest level, the objective is to form a set of completely autonomous units such that intercell movement of parts is minimized. We present an integer program that is solved using a genetic algorithm (GA) to assist in the design of cellular manufacturing systems. The formulation uses a unique representation scheme for individuals (part/machine partitions) that reduces the size of the cell formation problem and increases the scale of problems that can be solved. This approach offers improved design flexibility by allowing a variety of evaluation functions to be employed and by incorporating design constraints during cell formation. The effectiveness of the GA approach is demonstrated on several problems from the literature.
Minimization Subproblems and Heuristics for an Applied Clustering Problem
, 2001
"... A practical problem that requires the classification of a set of points of R^n using a criterion not sensitive to bounded outliers is studied in this paper. A fixedpoint (kmeans) algorithm is defined that uses an arbitrary distance function. Finite convergence is proved. A robust distance defined ..."
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Cited by 2 (1 self)
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A practical problem that requires the classification of a set of points of R^n using a criterion not sensitive to bounded outliers is studied in this paper. A fixedpoint (kmeans) algorithm is defined that uses an arbitrary distance function. Finite convergence is proved. A robust distance defined by Boente, Fraiman and Yohai is selected for applications. Smooth approximations of this distance are defined and suitable heuristics are introduced to enhance the probability of finding global optimizers. A reallife example is presented and commented.
A Hybrid Genetic Algorithm for Manufacturing Cell Formation
"... Cellular manufacturing emerged as a production strategy capable of solving the problems of complexity and long manufacturing lead times in batch production. The fundamental problem in cellular manufacturing is the formation of product families and machine cells. This paper presents a new approach fo ..."
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Cellular manufacturing emerged as a production strategy capable of solving the problems of complexity and long manufacturing lead times in batch production. The fundamental problem in cellular manufacturing is the formation of product families and machine cells. This paper presents a new approach for obtaining machine cells and product families. The approach combines a local search heuristic with a genetic algorithm. Computational experience with the algorithm on a set of group technology problems available in the literature is also presented. The approach produced solutions with a grouping efficacy that is at least as good as any results previously reported in literature and improved the grouping efficacy for 59 % of the problems. Keywords: Cellular Manufacturing; Group Technology; Genetic Algorithms; Random Keys AT&T Labs Research Technical Report TD5FE6RN, October 29, 2002.
MANUFACTURING CELL DESIGN WITH REDUCTION IN SETUP TIME THROUGH GENETIC ALGORITHM
"... Cellular manufacturing emerged as a production strategy capable of solving the problems of complexity and long manufacturing lead times in batch production. The fundamental problem in cellular manufacturing is the formation of product families and machine cells. This paper presents a new approach fo ..."
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Cellular manufacturing emerged as a production strategy capable of solving the problems of complexity and long manufacturing lead times in batch production. The fundamental problem in cellular manufacturing is the formation of product families and machine cells. This paper presents a new approach for obtaining simultaneous arrangement of part families and machine cells for cellular manufacturing systems. The main feature of the proposed method is, the relevant production data such as process sequences and setup times are taken in to account. It has the ability to select the best solution among the solutions of compactness, group technology efficiency and reducing setup time efficiency for each part before attempting to cluster the machines and parts. The formation of part family and machine cell has been treated as a maximization problem according to a defined performance measure ‘β’. A genetic algorithm has been developed for solving the cell formation problem considering the reduction in setup time. The validation has been done based on a real time manufacturing data. This algorithm is written in the ‘C’ language on Intel Pentium / PIII compatible system.
unknown title
, 2003
"... www.elsevier.com/locate/dsw Similarity coefficient methods applied to the cell formation problem: a comparative investigation ..."
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www.elsevier.com/locate/dsw Similarity coefficient methods applied to the cell formation problem: a comparative investigation
(AIRO 2011 Conference) A Column Generation Heuristic for MachinePart Cell Formation
"... The MachinePart Cell Formation is the problem of creating manufacture cells aiming best production flow of manageable subsystems. Systems automation and control can be improved by the aggregation of similar parts into families, and machines into independent cells that completely manufactures famil ..."
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The MachinePart Cell Formation is the problem of creating manufacture cells aiming best production flow of manageable subsystems. Systems automation and control can be improved by the aggregation of similar parts into families, and machines into independent cells that completely manufactures families of parts. The objective of the problem is to form a given number of disjoint partsmachines groups in which products do not have to move from one cell to the other to be processed. This problem be viewed as a clustering problem, and can be modeled as a pmedian location problem. This paper presents a column generation approach to pmedian problem, adapted to produce feasible assignments of parts into families. A further heuristic step assigns machines to families of parts to form the manufacturing cells. Experimental tests were made using instances from the literature. The computational results obtained with the heuristic were as good as in the literature for the majority of the instances, and even better in some cases.