Genetic algorithm-based subproblem solution procedures for a modified shifting bottleneck heuristic for complex job shops

Mönch, Lars; Schabacker, Rene; Pabst, Detlef; Fowler, John W.

doi:10.1016/j.ejor.2005.12.020

Cited by 90 publications

(29 citation statements)

References 20 publications

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“…For example, the solution: (O, O 11 , O 21 , O 31 , O 32 , O 12 , O 22 , O 23 , O 13 , O 33 , f) will contain a nodes sequence that represents the programming of the different operations for each job, as was illustrated in the first step of this methodology. Although, the first, second and third operation of each job can be done in any order, it is necessary to keep in mind that two operations from the same job cannot be done in a simultaneous manner, in two different work centers.…”

Section: Methodsmentioning

confidence: 99%

“…Currently, the use of hyperheuristics in the processes of production scheduling and programming in Job Shop environments has not been widely spread [4]. However, there are some hyperheuristics based on methodologies such as heuristics [5], algorithms [6][7][8][9][10], genetic algorithms [11][12][13][14], intelligent particles [15][16][17][18][19], ant colonies [20], immune systems [21], and others [22][23][24][25][26][27][28].…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

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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“…Algorithms like immediate selection and shifting bottleneck heuristics were proposed by Carlier [17], Adams [18], and Lars Monch [19]. And these algorithms were due to disjunctive graph model.…”

Section: Problem Formulationmentioning

confidence: 99%

A Promising Initial Population Based Genetic Algorithm for Job Shop Scheduling Problem

Jorapur¹,

Puranik²,

Deshpande³

et al. 2016

JSEA

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Job shop scheduling problem is typically a NP-Hard problem. In the recent past efforts put by researchers were to provide the most generic genetic algorithm to solve efficiently the job shop scheduling problems. Less attention has been paid to initial population aspects in genetic algorithms and much attention to recombination operators. Therefore authors are of the opinion that by proper design of all the aspects in genetic algorithms starting from initial population may provide better and promising solutions. Hence this paper attempts to enhance the effectiveness of genetic algorithm by providing a new look to initial population. This new technique along with job based representation has been used to obtain the optimal or near optimal solutions of 66 benchmark instances which comprise of varying degree of complexity.

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“…But there exist obvious drawbacks with some of these approaches. For instance, the algorithm presented in [2] encounters severe deterioration in the solution quality because it adds many extra constraints to each subproblem; the decomposition methods in [17,23,24] cannot guarantee the feasibility of subproblem solutions to the original problem and should rely on a heuristic coordination algorithm to construct a feasible solution for the original problem; some existing decompositionbased methods like [17,18,22] can hardly be applied to really large-scale job shop scheduling because the time complexity of these algorithms is unduly high. Besides, some other algorithms rely on (or are specifically designed to suit) the particular features of a special type of scheduling environment and thus they perform poorly for ordinary job shop problems without such special features.…”

mentioning

confidence: 99%

A hybrid approach to large-scale job shop scheduling

Zhang

2008

Appl Intell

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A decomposition based hybrid optimization algorithm is presented for large-scale job shop scheduling problems in which the total weighted tardiness must be minimized. In each iteration, a new subproblem is first defined by a simulated annealing approach and then solved using a genetic algorithm. We construct a fuzzy inference system to calculate the jobs' bottleneck characteristic values which depict the characteristic information in different optimization stages. This information is then utilized to guide the process of subproblem-solving in an immune mechanism in order to promote the optimization efficiency. Numerical computational results show that the proposed algorithm is effective for solving large-scale scheduling problems.

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Genetic algorithm-based subproblem solution procedures for a modified shifting bottleneck heuristic for complex job shops

Cited by 90 publications

References 20 publications

Design of a Hyperheuristic for Production Scheduling in Job Shop Environments

Design of a Hyperheuristic for Production Scheduling in Job Shop Environments

A Promising Initial Population Based Genetic Algorithm for Job Shop Scheduling Problem

A hybrid approach to large-scale job shop scheduling

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