A hybrid method for flowshops scheduling with condition-based maintenance constraint and machines breakdown

Safari, Ehram; Sadjadi, Seyed Jafar

doi:10.1016/j.eswa.2010.07.138

Cited by 37 publications

(22 citation statements)

References 40 publications

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“…One of the most important theories or assumptions in manufacturing programme of this study is considering the machines in a continuous and defect-less mode. Safari and Sajadi (2011) have proposed the present workshop conditions under those maintenances based on the conditions to minimise, as far as possible. They suggested a combinatory algorithm based on the genetic algorithm and simulated annealing.…”

Section: Literature Reviewmentioning

confidence: 99%

Selecting a preventive maintenance scheduling method by using simulation and multi criteria decision making

Eslami

Sajadi

Kashan

2014

IJLSM

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One of the major factors of competitive advantage in service and manufacturing systems is establishing a proper maintenance system .The productivity of the production line and equipment efficiency are among the significant points in most manufacturing companies which are directly related to their production style. Achieving the highest possible productivity improves the operations and functions of the line and finally increases the production volume. Various variables are effective on the productivity and efficiency of the line, among which, the preventive maintenances is one of the most important factors for cost reduction, equipment defect reduction, quality increase and efficiency increase. Multi-criteria decision-making methods are able to include and concern various variables related to competitive factors of a system. The purpose of this study is applying simulations to evaluate different scheduling techniques for preventive maintenances and combining the simulations as a decision-making tool, with the decision-making process. In this article three different preventive maintenance techniques have been implemented and simulated by using Arena-based simulation with a numerical example and finally, their results are compared with each other through TOPSIS and AHP, and the most efficient preventive maintenance technique is determined.

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Section: Literature Reviewmentioning

confidence: 99%

Selecting a preventive maintenance scheduling method by using simulation and multi criteria decision making

Eslami

Sajadi

Kashan

2014

IJLSM

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“…Based on a clonal selection principle and an affinity maturation mechanism of the immune response, they proposed an immune algorithm (IA) and applied the Taguchi parameter design method to analyze the proposed algorithm. Safari and Sadjadi [13] explored flowshop configuration under the assumption of condition-based maintenance to minimize expected makespan and proposed a conditionbased maintenance (CBM) strategy and a hybrid algorithm based on genetic algorithm and simulated annealing. Their simulation results showed its superiority.…”

Section: Introductionmentioning

confidence: 99%

A Discrete Group Search Optimizer for Hybrid Flowshop Scheduling Problem with Random Breakdown

Cui

2014

Mathematical Problems in Engineering

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The scheduling problems have been discussed in the literature extensively under the assumption that the machines are permanently available without any breakdown. However, in the real manufacturing environments, the machines could be unavailable inevitably for many reasons. In this paper, the authors introduce the hybrid flowshop scheduling problem with random breakdown (RBHFS) together with a discrete group search optimizer algorithm (DGSO). In particular, two different working cases, preempt-resume case, and preempt-repeat case are considered under random breakdown. The proposed DGSO algorithm adopts the vector representation and several discrete operators, such as insert, swap, differential evolution, destruction, and construction in the producers, scroungers, and rangers phases. In addition, an orthogonal test is applied to configure the adjustable parameters in the DGSO algorithm. The computational results in both cases indicate that the proposed algorithm significantly improves the performances compared with other high performing algorithms in the literature.

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“…Some studies used tailor-made genetic operators to enhance the ability of Genetic Algorithms (as discussed by Amin-Naseri and Afshari [247], Qing-Dao-Er-Ji and Wang [248,249], Qing-Dao-Er-Ji et al [250,251], and Ahmadizar and Farahani [52]); Ahmad et al [252] applied a problemspecific heuristic to improve the quality of initial solution; some other studies hybridized the Genetic Algorithm and some problem-specific local search schemes (as discussed by Do Ngoc et al [253], Tseng and Lin [254], and Vidal et al [135]) or neighborhood search procedures [255][256][257]. The majority of the hybrid methods are the combinations of different metaheuristics, such as the combination of Genetic Algorithm and Tabu Search procedures (as discussed by Zhang et al [258], Meeran and Morshed [259], Li and Gao [260], Yu et al [261], and Noori and Ghannadpour (2012)) and the integration of Genetic Algorithm and Simulated Annealing (as discussed by Safari and Sadjadi [262], Rafiei et al [263], and Bettemir and Sonmez [264]). In recent years, the combination of Genetic Algorithm and Particle Swarm Optimization (PSO) had been widely applied in both scheduling and vehicle routing problems (as discussed by Du et al [265], Yu et al [266], Liu et al [267], and Kumar and Vidyarthi [268]).…”

Section: Hybrid Metaheuristicsmentioning

confidence: 99%

A Survey of Recent Research on Optimization Models and Algorithms for Operations Management from the Process View

Fei

Shen

2017

Scientific Programming

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Over the past decades, optimization in operations management has grown ever more popular not only in the academic literature but also in practice. However, the problems have varied a lot, and few literature reviews have provided an overview of the models and algorithms that are applied to the optimization in operations management. In this paper, we first classify crucial optimization areas of operations management from the process point of view and then analyze the current status and trends of the studies in those areas. The purpose of this study is to give an overview of optimization modelling and resolution approaches, which are applied to operations management.

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A hybrid method for flowshops scheduling with condition-based maintenance constraint and machines breakdown

Cited by 37 publications

References 40 publications

Selecting a preventive maintenance scheduling method by using simulation and multi criteria decision making

Selecting a preventive maintenance scheduling method by using simulation and multi criteria decision making

A Discrete Group Search Optimizer for Hybrid Flowshop Scheduling Problem with Random Breakdown

A Survey of Recent Research on Optimization Models and Algorithms for Operations Management from the Process View

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