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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 ..."
Abstract

Cited by 16 (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.
(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.
A Manufacturing Cell Formation Algorithm with Minimum InterCell Movements
"... The main objective of this paper is to construct an algorithm for the formation of manufacturing cells with unbounded cell sizes, such that intercell movements are minimized. The assignment of parts to cells is then performed such that the number of exceptional parts is minimized. The solution of th ..."
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The main objective of this paper is to construct an algorithm for the formation of manufacturing cells with unbounded cell sizes, such that intercell movements are minimized. The assignment of parts to cells is then performed such that the number of exceptional parts is minimized. The solution of the algorithm starts from some initial conditions. A closed interval for the solution is then specified with a lower bound of the minimum intercell movements for the initial conditions and an upper bound on the intercell movements of the last cell. A combinatorial proof is provided to show that there exists at least one solution starting from the initial conditions.
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.
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.
AN INTEGRATED APPROACH OF ART1 AND TABU SEARCH TO SOLVE CELL FORMATION PROBLEMS
"... Adaptive resonance theory (ART1) network is one of the many popular neural networks used to solve the cell formation problem. Several modifications of ART1 for the problem have recently been published. In this study, a modified ART1 network is integrated with an effective optimization technique, Tab ..."
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Adaptive resonance theory (ART1) network is one of the many popular neural networks used to solve the cell formation problem. Several modifications of ART1 for the problem have recently been published. In this study, a modified ART1 network is integrated with an effective optimization technique, Tabu Search (TS), to solve cell formation problems. The number of exceptional elements (EE) and group efficiency (GE) are considered as the objectives for the problems under the constraints of the number of cells and cell size. This proposed heuristic (ART1&TS) first constructs a cell formation using a modified ART1, and then refines the solution using a basic TS heuristic. ART1&TS has been applied to most popular examples in the literature. The computational results showed that it generated the best solutions in most of the examples.