Minimizing makespan in a blocking flowshop using genetic algorithms

Caraffa, Vince; Ianes, Stefano; Bagchi, Tapan P.; Sriskandarajah, Chelliah

doi:10.1016/s0925-5273(99)00104-8

Cited by 141 publications

(73 citation statements)

References 18 publications

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“…The second variant of DE is the discrete DE (DDE) and the hybrid discrete DE (HDDE) of Ling et al (2010). The third algorithm is the GA of Caraffa et al (2001), and finally the TS and its multimoves (TS+M) variant of Grabowski and Pempera (2007).…”

Section: Termination and Starting Criteriamentioning

confidence: 99%

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Scheduling The Flow Shop With Blocking Problem With The Chaos-Induced Discrete Self Organising Migrating Algorithm

Davendra¹,

Bialic-Davendra²,

Šenkeřík³

et al. 2013

ECMS 2013 Proceedings Edited By: Webjorn Rekdalsbakken, Robin T. Bye, Houxiang Zhang

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Section: Termination and Starting Criteriamentioning

confidence: 99%

“…Comparison of DSOMA C with GA algorithm This comparison of the result of DSOMA C with that of GA algorithm of Caraffa et al (2001) is given in Table 5. For all the problem instances, DSOMA C produces better results for the PRD.…”

Section: Termination and Starting Criteriamentioning

confidence: 99%

Scheduling The Flow Shop With Blocking Problem With The Chaos-Induced Discrete Self Organising Migrating Algorithm

Davendra¹,

Bialic-Davendra²,

Šenkeřík³

et al. 2013

ECMS 2013 Proceedings Edited By: Webjorn Rekdalsbakken, Robin T. Bye, Houxiang Zhang

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“…Variance analysis was carried out under the model γ i = µ + Τ i + ε i, where γ i represents the variable of the response Τ i , the effect caused by the i th treatment, ε i, the i th experimental error indicate (Tables 12 y 13). With the literature reviewed in this study [50,51], it can be established that the design of hyperheuristics for finding a solution to sequencing problems in job shop environments has not been widely spread. However, it is notorious the use of some heuristics [52], but getting inferior results with the ones used in this analysis.…”

Section: Job Center 1 Job Center 7 Job Centermentioning

confidence: 99%

Design of a Hyperheuristic for Production Scheduling in Job Shop Environments

Castrillón

Sarache

Giraldo

2010

Ingeniare. Rev. chil. ing.

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RESUMENEl objetivo del presente trabajo es disminuir el tiempo de proceso (Makespan) e incrementar el tiempo de trabajo de las máquinas, diminuyendo el tiempo de ocio en ambientes de job shop, a través del diseño de una hiperheurística basada en colonia de hormigas y algoritmos genéticos. Este trabajo se desarrolla en dos etapas: en la primera se realiza la definición e identificación de una hiperheurística para la secuenciación de procesos en ambientes job shop. En la segunda etapa es mostrada la efectividad del sistema en la programación de la producción. En el proyecto de investigación se seleccionó una empresa del sector metalmecánico, donde por medio de una combinación de colonia de hormigas y algoritmos genéticos se programa la ruta óptima para un pedido, logrando la optimización o suboptimización de su respectivo tiempo total de proceso en un porcentaje superior al 95%.Palabras clave: Taller de trabajos, programación, heurísticas, simulación, función evaluación, tiempo total de proceso, tiempo ocioso. ABSTRACTThe objective of the present work is to diminish the total process time (Makespan)

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“…Many meta-heuristics based on Simulated Annealing can be found in Osman and Potts (1989), Ogbu and Smith (1990) and Ishibuchi et al (1995). Meta-heuristics based on Tabu Search techniques (Example: Nowicki & Smutnicki, 1996) and Evolutionary algorithms (Example: Reeves, 1995;Caraffa et al, 2001;Onwubolu & Davendra, 2006;Sayadi et al, 2010;Erdogmus, 2010) are also available in the literature.…”

Section: Introductionmentioning

confidence: 99%

Revisiting the NEH algorithm- the power of job insertion technique for optimizing the makespan in permutation flow shop scheduling

Baskar¹

2016

10.5267/j.ijiec

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Permutation flow shop scheduling problems have been an interesting area of research for over six decades. Out of the several parameters, minimization of makespan has been studied much over the years. The problems are widely regarded as NP-Complete if the number of machines is more than three. As the computation time grows exponentially with respect to the problem size, heuristics and meta-heuristics have been proposed by many authors that give reasonably accurate and acceptable results. The NEH algorithm proposed in 1983 is still considered as one of the best simple, constructive heuristics for the minimization of makespan. This paper analyses the powerful job insertion technique used by NEH algorithm and proposes seven new variants, the complexity level remains same. 120 numbers of problem instances proposed by Taillard have been used for the purpose of validating the algorithms. Out of the seven, three produce better results than the original NEH algorithm.

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Minimizing makespan in a blocking flowshop using genetic algorithms

Cited by 141 publications

References 18 publications

Scheduling The Flow Shop With Blocking Problem With The Chaos-Induced Discrete Self Organising Migrating Algorithm

Scheduling The Flow Shop With Blocking Problem With The Chaos-Induced Discrete Self Organising Migrating Algorithm

Design of a Hyperheuristic for Production Scheduling in Job Shop Environments

Revisiting the NEH algorithm- the power of job insertion technique for optimizing the makespan in permutation flow shop scheduling

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