A heuristic-search genetic algorithm for multi-stage hybrid flow shop scheduling with single processing machines and batch processing machines

Li, Dongni; Meng, Xianwen; Liang, Qiqiang; Zhao, Junqing

doi:10.1007/s10845-014-0874-y

Cited by 45 publications

(11 citation statements)

References 27 publications

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“…At the manufacturing level, optimal production planning and scheduling are developed to achieve energy conservation apparently [14], it is feasible in application and requires much less financial investment than other methods. Hybrid flow-shop scheduling problem (HFSP) refers to the optimal arrangement of production plan and resources to satisfy the requirements of specific goals, by means of adjusting of jobs processing sequence and allocating the parallel equipment reasonably [15], [16]. To this end, in this work, we proposed a sustainable production model for hybrid flow shop to reduce the production time, energy consumption and production cost in the scheduling, that is consistent with the current definition.…”

Section: Introductionmentioning

confidence: 76%

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A New Sustainable Scheduling Method for Hybrid Flow-Shop Subject to the Characteristics of Parallel Machines

LiMing

Wang

et al. 2020

IEEE Access

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Sustainable production for hybrid flow shop scheduling problem (HFSP) has attracted growing attention due to the environment and economy pressure in industry. As the major source of energyconsumption and cost, the selection of parallel machines for various jobs quite affect the sustainability in HFSP. However, the characteristic of parallel machines in job shops have not been addressed in current research, which hinder its practical application. Thus, in this work a novel sustainable HFSP model considering the characteristics of the machines is proposed through evaluation of the power, production efficiency and cost of the parallel machines. To solve this model, an improved genetic algorithm is developed, in which the matching distance between the parallel machines and the weights of the optimization objectives is introduced and integrated into iterations to accelerate the convergence. Finally, a case study is adopted to verify the proposed model and algorithm. Based on the optimization results, three kinds of typical scheduling modes, i.e., efficiency, energy-saving, and economic, are put forward to provide guidance for the sustainable production of hybrid flow-shop scheduling.

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Section: Introductionmentioning

confidence: 76%

“…The total amount of energy consumption can be obtained by summing up the processing energy of all operations as Eq. (15). (15) where E means the energy consumption.…”

Section: ) Production Makespanmentioning

confidence: 99%

A New Sustainable Scheduling Method for Hybrid Flow-Shop Subject to the Characteristics of Parallel Machines

LiMing

Wang

et al. 2020

IEEE Access

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“…A preliminary study of the specific industrial setup which motivated our research was done in Ackermann et al (2020+). For studies from different areas of application we refer, for instance, to Li et al (2015), Zhou et al (2016), Tan et al (2018), Chen et al (2019), Li et al (2019). The problems typically stem from various industries, e.g.…”

Section: Literaturementioning

confidence: 99%

Scheduling a proportionate flow shop of batching machines

Hertrich

Weiß

Ackermann

et al. 2020

J Sched

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In this paper we study a proportionate flow shop of batching machines with release dates and a fixed number $$m \ge 2$$ m ≥ 2 of machines. The scheduling problem has so far barely received any attention in the literature, but recently its importance has increased significantly, due to applications in the industrial scaling of modern bio-medicine production processes. We show that for any fixed number of machines, the makespan and the sum of completion times can be minimized in polynomial time. Furthermore, we show that the obtained algorithm can also be used to minimize the weighted total completion time, maximum lateness, total tardiness and (weighted) number of late jobs in polynomial time if all release dates are 0. Previously, polynomial time algorithms have only been known for two machines.

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“…It has been widely used to solve various optimization problems such as time dependent inventory routing problem (Cho et al 2014), yard crane scheduling , optimization for international logistics (Takeyasu and Kainosho 2014), scheduling of JIT cross-docking systems ), straight and U-shaped assembly line balancing (Alavidoost et al 2014), hybrid flow shop scheduling with single and batch processing machines (Li et al 2014), etc. In addition many researchers have applied genetic algorithms to solve the parallel machine scheduling problems.…”

Section: Genetic Algorithm (Ga)mentioning

confidence: 99%

Design of an efficient genetic algorithm for resource-constrained unrelated parallel machine scheduling problem with machine eligibility restrictions

Afzalirad

Shafipour

2015

J Intell Manuf

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This study addresses a resource-constrained unrelated parallel machine scheduling problem with machine eligibility restrictions. Majority of the traditional scheduling problems in parallel machine environment deal with machine as the only resource. However, other resources such as labors, tools, jigs, fixtures, pallets, dies, and industrial robots are not only required for processing jobs but also are often restricted. Considering other resources makes the scheduling problems more realistic and practical to implement in manufacturing environments. First, an integer mathematical programming model with the objective of minimizing makespan is developed for this problem. Noteworthy, due to NP-hardness of the considered problem, application of meta-heuristic is avoidable. Furthermore, two new genetic algorithms including a pure genetic algorithm and a genetic algorithm along with a heuristic procedure are proposed to tackle this problem. With regard to the fact that appropriate design of the parameters has a significant effect on the performance of algorithms, hence, we calibrate the parameters of these algorithms by using the response surface method. The performance of the proposed algorithms is evaluated by a number of numerical examples. The computational results demonstrated that the proposed genetic algorithm is an effective and appropriate approach for our investigated problem.

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A heuristic-search genetic algorithm for multi-stage hybrid flow shop scheduling with single processing machines and batch processing machines

Cited by 45 publications

References 27 publications

A New Sustainable Scheduling Method for Hybrid Flow-Shop Subject to the Characteristics of Parallel Machines

A New Sustainable Scheduling Method for Hybrid Flow-Shop Subject to the Characteristics of Parallel Machines

Scheduling a proportionate flow shop of batching machines

Design of an efficient genetic algorithm for resource-constrained unrelated parallel machine scheduling problem with machine eligibility restrictions

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