An improved sheep flock heredity algorithm for job shop scheduling and flow shop scheduling problems

Anandaraman, Chandramouli

doi:10.5267/j.ijiec.2011.06.007

Cited by 11 publications

(7 citation statements)

References 30 publications

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“…During this enhanced SFHA, having the mutation rate of the single point mutation is way to manage thereby enhancing the local search behavior. Second, a brand new robust-replace heuristic is introduced to assist in up the solution search of the algorithm among the global domain [12].…”

Section: Sheep Flock Heredity Algorithmmentioning

confidence: 99%

Optimization of Linear Layout Problem in Flexible Manufacturing System Using Evolutionary Algorithms - Case Study

Saravanan¹,

Kumar²,

Raman³

2015

AMM

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Linear layout is the commonly major preferred arrangement of the flexible manufacturing systems (FMS). The proposed enhanced sheep flock heredity algorithm to solving the unequal area linear layout problem through the real case study problem. The proposed model is to minimize the transportation cost with non-overlapping. Computational results show that proposed sheep flock heredity algorithm (SFHA) can obtain better than particle swarm optimization (PSO) and existing method.

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Section: Sheep Flock Heredity Algorithmmentioning

confidence: 99%

Optimization of Linear Layout Problem in Flexible Manufacturing System Using Evolutionary Algorithms - Case Study

Saravanan¹,

Kumar²,

Raman³

2015

AMM

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“…GA has been used in a wide variety of applications, particularly in combinatorial optimization problems and they were proved to be able to provide near optimal solutions in reasonable time (Anandaraman, 2011;Luo et al, 2011;Chakrabortty et al, 2013). A GA starts with a population of randomly generated candidate solutions (called chromosomes).…”

Section: The Proposed Ga Algorithmmentioning

confidence: 99%

Some heuristics for the hybrid flow shop scheduling problem with setup and assembly operations

Hosseini¹,

Jolai²

2013

10.5267/j.ijiec

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This paper presents a two-stage hybrid flow shop scheduling problem with setup and assembly operations. The proposed study of this paper considers one kind of product with a quantity of demand where each product is made by assembling a set of different parts. At first, the parts are manufactured in a two-stage hybrid flow-shop and then the parts are assembled into products on assembly stage. Setup operations are needed when a machine starts processing the parts or it changes items. The considered objective is minimizing the completion time of all products. Since the problem is classified as NP-hard class, a combinatorial algorithm is proposed. The proposed algorithm is a three-step procedure where we use heuristic, genetic algorithm (GA), simulated annealing (SA), NEH and Johnson's algorithm. Three lower bounds are presented and improved to evaluate the proposed algorithms. An extensive computational experiment is conducted to compare the performances of the proposed algorithms.

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“…El segundo aplica sí una o más máquinas deben realizar operaciones diferentes (Medina et al, 2011). El tercero analiza los problemas de Programación tipo "Job Shop" y "Flow Shop", generando un algoritmo hereditario que minimiza el tiempo de proceso (Anandaraman, 2011).…”

Section: Problemas Del Tipo Job Shopunclassified

Programación Multiobjetivo en un Sistema de Fabricación Tipo "Contra Existencia" (Job Shop)

2013

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ResumenEn el presente artículo se analiza el desempeño de las variables tiempo de procesamiento, fracción defectuosa causada por la fatiga del operario y costo de mano de obra directa, en un sistema tipo "contra existencia" (job shop). Con el anterior propósito se comparan dos métodos, el primero toma elementos de los algoritmos VEGA y MOGA (VyM), mientras que el segundo corresponde a un método de sumas ponderadas (MSP). Al aplicar las metodologías se encontró que el método VyM presenta mejor desempeño al compararlo con el MSP. Respecto al tiempo de proceso (en horas) el primero supera al segundo en 7.0 %; respecto al tiempo de proceso (en semanas) el primero supera al segundo en 6.7 % y respecto a la fracción defectuosa, el primero supera al segundo en 1,4 %. En cuanto al costo de mano de obra, ambos métodos presentan igual desempeño. Palabras clave: multiobjetivo, algoritmos genéticos, moga, job shop, tiempo de procesamiento Multiobjective Programming in a Manufacturing System of the Job Shop Type AbstractIn this paper, the performance of the variables: makespan time, defective fraction due to operator fatigue and direct labor cost, in a job shop manufacturing system is presented. Two methods are compared; the first one blends elements from VEGA and MOGA algorithms (V&M), while the second one corresponds to a weighted sums method (WSM). Applying these methodologies, it was found that the method V&M has a better performance than the WSM. Comparing he variable makespan time (in hours) the first is better by 7.0 %; comparing the variable makespan time (in weeks) by 6.7 %; and comparing the variable defective fraction by 1.4 %. Regarding the variable labor costs, both methods have the same performance.

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An improved sheep flock heredity algorithm for job shop scheduling and flow shop scheduling problems

Cited by 11 publications

References 30 publications

Optimization of Linear Layout Problem in Flexible Manufacturing System Using Evolutionary Algorithms - Case Study

Optimization of Linear Layout Problem in Flexible Manufacturing System Using Evolutionary Algorithms - Case Study

Some heuristics for the hybrid flow shop scheduling problem with setup and assembly operations

Programación Multiobjetivo en un Sistema de Fabricación Tipo "Contra Existencia" (Job Shop)

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