Efficiency of the solution representations for the hybrid flow shop scheduling problem with makespan objective

Fernández-Viagas, Victor

doi:10.1016/j.cor.2019.05.002

Cited by 68 publications

(13 citation statements)

References 54 publications

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“…For the considered problem, different MIP models and lower bounds are proposed in the literature; however, they are likely to be compared using different conditions or not compared with other methods. Motivated by the study of Naderi et al [13] and the testbeds proposed by Fernandez-Viagas et al [16], this study develops a MIP model for 𝐻𝐹 𝑘 //𝐶 𝑚𝑎𝑥 problems to obtain optimal solutions as benchmarks and provides a fair comparison with the existing MIP models for the 𝐻𝐹 𝑘 //𝐶 𝑚𝑎𝑥 problem using the same test instances. Moreover, we propose two lower-bound methods as strong indicators when the optimal solutions cannot be obtained.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Our study considers the problem of 𝐻𝐹 𝑘 //𝐶 𝑚𝑎𝑥 due to its significance in both NP-hard features and production applications, and we formulate a new MIP model and two lower-bound methods. In addition, we adopt the same testbeds proposed by Fernandez-Viagas et al [16] to fairly examine the performance of the MIP models and obtain a detailed benchmark for all instances in the testbeds. Regarding lower bounds, we make two propositions to analyze their dominances and further suggest a better lower bound calculation.…”

Section: Introductionmentioning

confidence: 99%

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An Evaluation of Mathematical Programming and Lower-Bound Methods for Hybrid Flow Shop Problems With a Makespan Criterion

2023

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This paper considers the hybrid flow shop scheduling problem, where jobs are processed in m stages with the same route of the stage. Each stage has identical parallel machines for processing jobs. Some mathematical programming formulations and lower bound calculations have been proposed in the literature for such cases. Nevertheless, there is a lack of complete comparisons of these mathematical programming formulations and lower bounds in the hybrid flow shop literature. In this paper, we propose a new mixed integer programming model and two new lower bounds based on the bin-packing concept for the considered problem. To evaluate the proposed model, two sets of small and small-to-medium problems are used to compare our model with the existing models. Moreover, two propositions are discussed for lower bounds. The experimental results show that the proposed mixed integer programming model efficiently found optimal solutions because it needs a smaller number of binary variables and a smaller number of constraints, and the proposed lower bound can also serve as a strong indicator to evaluate the distances between the solutions obtained by heuristic algorithms and the optimal solution.INDEX TERMS hybrid flow shop, makespan, mixed integer programming, lower bound

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Evaluation of Mathematical Programming and Lower-Bound Methods for Hybrid Flow Shop Problems With a Makespan Criterion

2023

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“…Equation ( 5) illustrates the relationship between the start time and the completion time of the process at the same stage. Equation (6) indicates that the next process of the same job cannot be started before the previous process is completed.…”

Section: Decision Variablesmentioning

confidence: 99%

“…Traditional workshop scheduling problems usually consider a single economic indicator, while green and economic indicator are both considered green manufacturing [5]. Green indicators usually contain minimizing the consumption of resources and minimizing the impact on the environment [6]. Due to most of the production methods of chemical, steel, and other high-profile production methods being flowing operations, the similar processing production processes can be abstracted as a hybrid flow-shop scheduling problem (HFSP) [7].…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Hybrid Flow-Shop Scheduling under Time-of-Use and Ladder Electricity Tariffs

Chen

Wang

et al. 2022

Applied Sciences

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With the increasing influence of climate change, green development has become an important trend. Since manufacturing represents approximately one-half of total energy consumption, reducing the amount of energy consumed within this industry is imperative. This study provides a hybrid flow shop scheduling issue under a time-of-use and ladder electricity price system to reduce total energy consumption without compromising maximum completion time. An improved non-dominated sorting genetic algorithm II with some optimization strategies is proposed to solve the problem. First, an enhanced constructive heuristic algorithm is used to improve the quantity of initial solution in the initialization. Besides, an adaptive genetic operation is introduced, aiming to avoid the emergence of locally optimal solutions. In addition, the right-shift approach is developed to reduce the total energy consumption without affecting completion time. By maintaining the production efficiency and reducing the energy consumption cost by 4.33%. A trade-off proposal is made between productivity and sustainability in view of the calculation results.

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“…In the flow shop scheduling problems, a series of jobs are ordered, and each job employs one machine in each stage [12] [13]. However, in HFSS, a series of jobs have similar production orders, but each stage's job might require one or more machines [14] [15].…”

Section: Introductionmentioning

confidence: 99%

Energy-Aware Scheduling in Hybrid Flow Shop using Firefly Algorithm

Jabari

Hasan

2021

JTI

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Nowadays, the industrial sector takes up a significant portion of the world's total energy consumption. This sector is responsible for half of the total energy consumed in the world. Therefore, efficiency in the industrial sector becomes an essential issue. One of the main factors triggering the high energy consumption in this sector is that many machines are left idle. Idle machines during the manufacturing process require electricity and other energies. This research aimed to develop a firefly algorithm that can minimize the energy consumption in the hybrid flow shop scheduling problem. This algorithm is used to determine the optimum order of the jobs. The ultimate goal is to minimize energy consumption. The experiment on the algorithm was conducted by employing iteration and population variations. The research results show that population and iteration affect the quality of the hybrid flow shop scheduling solution.

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Efficiency of the solution representations for the hybrid flow shop scheduling problem with makespan objective

Cited by 68 publications

References 54 publications

An Evaluation of Mathematical Programming and Lower-Bound Methods for Hybrid Flow Shop Problems With a Makespan Criterion

An Evaluation of Mathematical Programming and Lower-Bound Methods for Hybrid Flow Shop Problems With a Makespan Criterion

Energy-Efficient Hybrid Flow-Shop Scheduling under Time-of-Use and Ladder Electricity Tariffs

Energy-Aware Scheduling in Hybrid Flow Shop using Firefly Algorithm

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