Designing cellular manufacturing systems under dynamic and uncertain conditions

Safaei, Nima; Saidi‐Mehrabad, Mohammad; Babakhani, Masoud

doi:10.1007/s10845-007-0029-5

Cited by 26 publications

(8 citation statements)

References 19 publications

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“…Autores como Defersha (2006) partieron de un modelo probabilístico para dar solución al problema de FC mediante el método de descomposición de Benders, mientras que Ho (2011) emplea programación matemática; Mahdavi (2010), programación lineal entera, mientras que Safaei (2007) genera una posible solución mediante programación difusa.…”

Section: Tipos Y Métodos De Soluciónunclassified

Modelos matemáticos para la definición del layout de las celdas de manufactura. Revisión de literatura

Duque

Moncayo

Martínez

2015

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El presente artículo de revisión aborda el planteamiento del problema del layout de las celdas de manufactura (LCM) de una forma descriptiva, considerando primero el problema y sus variaciones, luego los elementos de los modelos matemáticos, y posteriormente los métodos de solución empleados; y por último se concluye con algunas perspectivas futuras alrededor de este tema. Palabras clave: Celdas de manufactura, Formación de celdas, Layout, Métodos de solución. AbstractThis review article discusses the approach to the layout problem of cell manufacturing (LCM) in a descriptive form; considering at first the problem and its variations, then the elements of the mathematical models, subsequently presenting solution methods used; and finally some future perspectives about this topic are considered.

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Section: Tipos Y Métodos De Soluciónunclassified

Modelos matemáticos para la definición del layout de las celdas de manufactura. Revisión de literatura

Duque

Moncayo

Martínez

2015

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“…They considered alternative routings, lot splitting and sequence of operations as well as workload balancing in their model. Safaei et al [7] presented a fuzzy programming approach in CMS with dynamic and uncertain condition. The authors in this study assumed that demand of parts and availability of each machine have uncertain and fuzzy condition.…”

Section: Literature Reviewmentioning

confidence: 99%

A Multi-objective Mathematical Model Considering Economic and Social Criteria in Dynamic Cell Formation

Niakan¹,

Baboli²,

Moyaux³

et al. 2014

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

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Part 1: Knowledge-Based SustainabilityInternational audienceThis paper addresses a Dynamic Cellular Manufacturing Systems (DCMS) problem considering both economic and social criteria, that is, the problem deals with the minimization of the total costs and maximization of social issues. We develop a bi-objective mathematical model of this problem in order to capture the trade-off between these two objectives. The strategic decisions considered in the model define the configuration of cells and part-families in each period. In order to solve our model, we design a new Non-dominated Sorting Genetic Algorithm (NSGA-II) as a meta-heuristic method. Our approach is illustrated on two samples of problems randomly generated

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“…Heuristic algorithms were implemented to minimize the sum of three cost components including the production cost of parts, the amortized cost of machines, and the relocating cost of machines during periods. Safaei et al [20] assumed that part demands and machine capacities were fuzzy numbers. Then, they formulated a dynamic CMS model.…”

Section: Introductionmentioning

confidence: 99%

A two-stage stochastic model for designing cellular manufacturing systems with simultaneous multiple processing routes and subcontracting

2017

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Abstract. In recent decades, many researchers have studied the cellular manufacturing system with consideration of various issues such as scheduling, production planning, layout, reliability, etc. However, limited research papers have investigated this problem in an uncertain environment. The present paper addresses a stochastic problem in cellular manufacturing systems considering simultaneous multiple routings and subcontracting. In the developed problem, each part can be simultaneously produced in multiple processing routes. It is also assumed that the unsatis ed part demands as a result of limited machine capacity or high manufacturing cost could be outsourced. A two-stage stochastic programming approach is employed to take the uncertainty into consideration and to formulate the problem. The objective function is to minimize the summation of production, subcontracting, material handling, and machine idleness costs. A sample average approximation method is applied as a solution method. Also, for further illustration of the problem, a numerical example is solved and sensitivity analyses are conducted. Finally, through some numerical examples extracted from related literature, the advantages of constructing a stochastic optimization model for the problem are demonstrated.

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Designing cellular manufacturing systems under dynamic and uncertain conditions

Cited by 26 publications

References 19 publications

Modelos matemáticos para la definición del layout de las celdas de manufactura. Revisión de literatura

Modelos matemáticos para la definición del layout de las celdas de manufactura. Revisión de literatura

A Multi-objective Mathematical Model Considering Economic and Social Criteria in Dynamic Cell Formation

A two-stage stochastic model for designing cellular manufacturing systems with simultaneous multiple processing routes and subcontracting

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