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1

A shuffled frog leaping algorithm with q-learning for distributed hybrid flow shop scheduling problem with energy-saving

Cai Jingcao, Wang Lei

Journal of Artificial Intelligence and Soft Computing Research

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2024

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Vol. 14, No. 2

101--120

EN

Energy saving has always been a concern in production scheduling, especially in distributed hybrid flow shop scheduling problems. This study proposes a shuffled frog leaping algorithm with Q-learning (QSFLA) to solve distributed hybrid flow shop scheduling problems with energy-saving(DEHFSP) for minimizing the maximum completion time and total energy consumption simultaneously. The mathematical model is provided, and the lower bounds of two optimization objectives are given and proved. A Q-learning process is embedded in the memeplex search of QSFLA. The state of the population is calculated based on the lower bound. Sixteen search strategy combinations are designed according to the four kinds of global search and four kinds of neighborhood structure. One combination is selected to be used in the memeplex search according to the population state. An energy-saving operator is presented to reduce total energy consumption without increasing the processing time. One hundred forty instances with different scales are tested, and the computational results show that QSFLA is a very competitive algorithm for solving DEHFSP.

2

Minimizing the Makespan and Total Tardiness in Hybrid Flow Shop Scheduling with Sequence-Dependent Setup Times

Mousavi Seyyed Mostafa, Shahnazari-Shahrezaei Parisa

Management and Production Engineering Review

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2023

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Vol. 14, No. 1

13--24

EN

The paper considers the production scheduling problem in a hybrid flow shop environment with sequence-dependent setup times and the objectives of minimizing both the makespan and the total tardiness. The multi-objective genetic algorithm is applied to solve this problem, which belongs to the non-deterministic polynomial-time (NP)-hard class. In the structure of the proposed algorithm, the initial population, neighborhood search structures and dispatching rules are studied to achieve more efficient solutions. The performance of the proposed algorithm compared to the efficient algorithm available in literature (known as NSGA-II) is expressed in terms of the data envelopment analysis method. The computational results confirm that the set of efficient solutions of the proposed algorithm is more efficient than the other algorithm.

3

An optimum scheduling method for multi-option product flows through production lineswithout intermediate buffers

Magiera Marek

Management and Production Engineering Review

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2020

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Vol. 11, No. 1

86--94

EN

The presented method is constructed for optimum scheduling in production lines with parallel machines and without intermediate buffers. The production system simultaneously performs operations on various types of products. Multi-option products were taken into account – products of a given type may differ in terms of details. This allows providing for individual requirements of the customers. The one-level approach to scheduling for multioption products is presented. The integer programming is used in the method – optimum solutions are determined: the shortest schedules for multi-option products. Due to the lack of the intermediate buffers, two possibilities are taken into account: no-wait scheduling, possibility of the machines being blocked by products awaiting further operations. These two types of organizing the flow through the production line were compared using computational experiments, the results of which are presented in the paper.

4

Comparative simulation study of production scheduling in the hybrid and the parallel flow

Varela M. L. R., Trojanowska J., Carmo-Silva S., Costa N. M. L., Machado J.

Management and Production Engineering Review

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2017

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Vol. 8, No. 2

69--80

EN

Scheduling is one of the most important decisions in production control. An approach is proposed for supporting users to solve scheduling problems, by choosing the combination of physical manufacturing system configuration and the material handling system settings. The approach considers two alternative manufacturing scheduling configurations in a two stage product oriented manufacturing system, exploring the hybrid flow shop (HFS) and the parallel flow shop (PFS) environments. For illustrating the application of the proposed approach an industrial case from the automotive components industry is studied. The main aim of this research to compare results of study of production scheduling in the hybrid and the parallel flow, taking into account the makespan minimization criterion. Thus the HFS and the PFS performance is compared and analyzed, mainly in terms of the makespan, as the transportation times vary. The study shows that the performance HFS is clearly better when the work stations’ processing times are unbalanced, either in nature or as a consequence of the addition of transport times just to one of the work station processing time but loses advantage, becoming worse than the performance of the PFS configuration when the work stations’ processing times are balanced, either in nature or as a consequence of the addition of transport times added on the work stations’ processing times. This means that physical layout configurations along with the way transport time are including the work stations’ processing times should be carefully taken into consideration due to its influence on the performance reached by both HFS and PFS configurations.

5

A version of cooperative multi-swarm PSO using electoral mechanism to solve hybrid flow shop scheduling problem

Li D., He Q.

Przegląd Elektrotechniczny

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2012

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R. 88, nr 5b

22-26

EN

Hybrid flow shop (HFS) scheduling problem is a kind of scheduling consisted of a series of stages, in which there exist more than one parallel machine. In this paper, we propose a meta-heuristics using a version of cooperative multi-swarm PSO algorithm for the HFS with minimum makespan objective. The main contribution of this algorithm is to import an electoral mechanism to accelerate the converging and a disturbance approach to help escape from local optima. Finally, experiments show that the algorithm outperforms all the compared in the HFS problem.

PL

W artykule zaproponowano nowy rojowy algorytm do rozwiązywania problemu w harmonogramie dostępu typu HFS. Nowy mechanizm wyboru pozwala na przyśpieszenie konwergencji.

6

A Genetic algorithm to minimize the makespan in the k-stage hybrid flow shop scheduling problem

Besbes W., Teghem J., Loukil T.

Foundations of Computing and Decision Sciences

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2010

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Vol. 35, No. 1

3-24

EN

In this paper, we consider the k-stage hybrid flow shop scheduling problem where the parallel machines are identical. Our study aims to provide a good approximate solution to this specific problem with the makespan (Cmax) minimization as the objective function. Considering the success of the Genetic Algorithms (GA) developed for scheduling problems, we apply this metaheuristic to deal with this problem. We develop a GA with a new crossover operator. Indeed, it is a combination of two other crossover operator proposed in the literature. The design of our GA is different compared to the classical structure of the genetic algorithm especially in the encoding of solutions. For the calibration of our metaheuristic parameters, we conduct several experimental designs. Our algorithm is tested on a well known benchmark in the literature. The numerical results show that the proposed genetic algorithm is an efficient approach for solving the k-stage hybrid flow shop problem. Furthermore, this computational study shows that our GA, with the proposed crossover operator gives better results than the two other crossover operators.