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27
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 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.
Grouping Components In Printed Circuit Board Assembly with Limited . . .
 INT. J. PROD. RES.
, 1997
"... ..."
Utilizing Lamarckian Evolution and the Baldwin Effect in Hybrid Genetic Algorithms
, 1996
"... Genetic algorithms(GA) are very efficient at exploring the entire search space; however, they are relatively poor at finding the precise local optimal solution in the region at which the algorithm converges. Hybrid genetic algorithms are the combination of improvement procedures, usually working as ..."
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Cited by 3 (1 self)
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Genetic algorithms(GA) are very efficient at exploring the entire search space; however, they are relatively poor at finding the precise local optimal solution in the region at which the algorithm converges. Hybrid genetic algorithms are the combination of improvement procedures, usually working as evaluation functions, and genetic algorithms. There are two basic strategies in using hybrid GAs, Lamarckian and Baldwinian learning. Traditional schema theory does not support Lamarckian learning, i.e., forcing the genetic representation to match the solution found by the improvement procedure. However, Lamarckian learning does alleviate the problem of multiple genotypes mapping to the same phenotype. Baldwinian learning uses improvement procedures to change the fitness landscape, but the solution that is found is not encoded back into the genetic string. This paper empirically examines the issues of using Lamarckian and Baldwinian learning in hybrid GAs. In the empirical investigation cond...
Integrating Design And Planning Considerations In Cellular Manufacturing
"... This paper presents a new model that integrates design and planning to prescribe a costeffective cellular configuration that is responsive to real world considerations. The model incorporates practical engineering features such as the finite capacity of machines, use of alternative machines, multip ..."
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Cited by 1 (0 self)
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This paper presents a new model that integrates design and planning to prescribe a costeffective cellular configuration that is responsive to real world considerations. The model incorporates practical engineering features such as the finite capacity of machines, use of alternative machines, multiple "copies" of a machine type, and limitations on cell size. It integrates design decisions, locating machines in each cell and identifying product families, with planning considerations, assuring that machine capacities are sufficient to produce required volumes and dealing with between cell movement to use alternative machines. Computational experience using a commercially available optimization package demonstrates that run time required to resolve problems of realistic size and scope can be quite reasonable.
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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Cited by 1 (1 self)
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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...
SOCIAL NETWORKS Cliques, Galois lattices, and the structure
"... The mathematical definition of clique has never been entirely satisfactory when it comes to providing a procedure for defining human social groups. This paper shows how the Galois structure of containment among cliques and actors can be used to produce an intuitively appealing characterization of gr ..."
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The mathematical definition of clique has never been entirely satisfactory when it comes to providing a procedure for defining human social groups. This paper shows how the Galois structure of containment among cliques and actors can be used to produce an intuitively appealing characterization of groupsone that is consistent with ethnographic descriptions. Two examples, using 'classical ' social network data sets, are provided. 1.
Annals of Operations Research 65(1996)3554 35 Manufacturing cell formation by statespace search*
"... This paper addresses the problem of grouping machines in order to design cellular manufacturing ceils, with an objective to minimize intercell flow. This problem is related to one of the major aims of group technology (GT): to decompose the manufacturing system into manufacturing cells that are as ..."
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This paper addresses the problem of grouping machines in order to design cellular manufacturing ceils, with an objective to minimize intercell flow. This problem is related to one of the major aims of group technology (GT): to decompose the manufacturing system into manufacturing cells that are as independent as possible. This problem is NPhard. Thus, nonheuristic methods cannot address problems of typical industrial dimensions because they would require exorbitant amounts of computing time, while fast heuristic methods may suffer from poor solution quality. We present a branchandbound statespace search algorithm that attempts to overcome both these deficiencies. One of the major strengths of this algorithm is its efficient branching and search strategy. In addition, the algorithm employs the fast InterCell Traffic Minimization Method to provide good upper bounds, and computes lower bounds based on a relaxation of merging.
“Evaluation and optimization of innovative production systems of goods and services” STUDY OF DIFFERENT PRINCIPLES FOR AUTOMATIC IDENTIFICATION OF GENERALIZED SYSTEM OF CONTRADICTIONS OUT OF DESIGN OF EXPERIMENTS
"... ABSTRACT: Problems in design of technical systems can be solved by optimization or inventive solving principles. Two representation models are studied: Generalized System of Contradictions (GSC) as inventive principle and Design of Experience (DoE) as optimisation principle. Our purpose is to improv ..."
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ABSTRACT: Problems in design of technical systems can be solved by optimization or inventive solving principles. Two representation models are studied: Generalized System of Contradictions (GSC) as inventive principle and Design of Experience (DoE) as optimisation principle. Our purpose is to improve the capacity of design problems resolution by using the both solving principles articulated to one representation model. We will show how it is possible to shift from DoE representation model to GSC representation model by using different methods. On the one side this transition can be done by the identification of Generalized System of Contradictions out of Design of Experiments based on a set of equations to resolve. On the other side methods of data analysis can be used to visualise and reorganise the DoE matrix in the form of “contradiction blocks ” reflecting the set of equations. This reorganisation of representation model will be illustrated on a simple technical system.