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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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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.
Recent developments in evolutionary computation for manufacturing optimization: Problems, solutions, and comparisons
 IEE Transactions on Evolutionary Computation
"... Abstract—The use of intelligent techniques in the manufacturing field has been growing the last decades due to the fact that most manufacturing optimization problems are combinatorial and NP hard. This paper examines recent developments in the field of evolutionary computation for manufacturing opti ..."
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Abstract—The use of intelligent techniques in the manufacturing field has been growing the last decades due to the fact that most manufacturing optimization problems are combinatorial and NP hard. This paper examines recent developments in the field of evolutionary computation for manufacturing optimization. Significant papers in various areas are highlighted, and comparisons of results are given wherever data are available. A wide range of problems is covered, from job shop and flow shop scheduling, to process planning and assembly line balancing. Index Terms—Assembly lines, cellular manufacturing, design, evolutionary computation, genetic algorithms, manufacturing optimization, process planning, scheduling. I.
Grouping Components In Printed Circuit Board Assembly with Limited . . .
 INT. J. PROD. RES.
, 1997
"... ..."
A Column Generation Approach to Cell Formation Problems in Cellular Manufacturing
"... Cellular manufacturing is a promising approach for grouping eciency in manufacturing systems. Although this problem has been extensively studied in the literature, very few authors have proposed exact methods. The basic cellular manufacturing problem consists in dening cells which lead to the min ..."
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Cellular manufacturing is a promising approach for grouping eciency in manufacturing systems. Although this problem has been extensively studied in the literature, very few authors have proposed exact methods. The basic cellular manufacturing problem consists in dening cells which lead to the minimum number of bottleneck elements. In this paper, we consider a new formulation of the cellular manufacturing problem where each variable corresponds to a potential cell. In order to deal with the large number of variables, we propose a solution scheme based on column generation techniques. We discuss its eciency and compare it with other exact methods proposed in the literature. Keywords: Group technology, cell formation, column generation, bottleneck parts. Resume La formation de cellules de production est une approche prometteuse pour eectuer des groupements ecaces dans les systemes manufacturiers. Bien que ce probleme ait ete beaucoup etudie dans la litterature, peu...
Constructive Genetic Algorithm for MachinePart Cell Formation
, 2000
"... This paper presents a new evolutionary approach to the machinepart cell formation (MPCF) problem, generally considered in manufacturing cell design, where a zeroone machinepart matrix must have its rows and columns moved to form machines and parts clusters. The Constructive Genetic Algorithm (CGA ..."
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This paper presents a new evolutionary approach to the machinepart cell formation (MPCF) problem, generally considered in manufacturing cell design, where a zeroone machinepart matrix must have its rows and columns moved to form machines and parts clusters. The Constructive Genetic Algorithm (CGA) was proposed recently to solve clustering problems, and is applied here to the MPCF. The MPCF is modeled as a biobjective problem that guides the construction of feasible assignments of machines and parts to specify clusters, and provides evaluation of schemata and structures in a common basis. A particularly derived structure and schema representation considers Jaccard distances for binary strings. A variable size population is formed only by schemata, considered as building blocks for feasible solutions construction along the generations. Recombination gives population diversification, and local search mutation is applied to structures that represent feasible solutions. Experimental res...
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.
(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.
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"... Experiences of a small to medium size enterprise in the design and implementation of manufacturing cells ..."
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Experiences of a small to medium size enterprise in the design and implementation of manufacturing cells
Merits of the Production Volume Based Sinlilarity Coefficient in Machine Cell Formation
"... In this paper, two types of similarity coefficients are com pared: (1) the Jaccard's coefficient and (2) the production volume based coefficient. Each is used to form a cellular manufacturing system whose performance will be used as a measure of effectiveness of the similarity coefficient. The ..."
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In this paper, two types of similarity coefficients are com pared: (1) the Jaccard's coefficient and (2) the production volume based coefficient. Each is used to form a cellular manufacturing system whose performance will be used as a measure of effectiveness of the similarity coefficient. The sum of intercellular and intracellular material handling costs is used as a criterion for performance evaluation.
www.elsevier.com/locate/dsw An evolutionary algorithm for manufacturing cell formation *
, 2003
"... Cellular manufacturing emerged as a production strategy capable of solving the certain 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 app ..."
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Cellular manufacturing emerged as a production strategy capable of solving the certain 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. q 2004 Published by Elsevier Ltd.