Solving Scheduling Problems in Case of Multi-objective Production Using Heuristic Optimization

Musiał, Kamil; Balashov, Artem; Burduk, Anna; Batako, Andre; Safonyk, Andrii

doi:10.1007/978-3-030-99310-8_2

Cited by 2 publications

(4 citation statements)

References 15 publications

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“…The final algorithm that was considered in this paper was the Tabu search [ 25 , 26 , 27 ], which is presented below on Figure 11 . More specifically, it is the simplest variation without accelerations or randomizing parameters, with the length of the Tabu list being 10 elements.…”

Section: Resultsmentioning

confidence: 99%

Composite Lamina Model Design with the Use of Heuristic Optimization

2023

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In engineering practice, a problem is quite often faced in which the number of unknown parameters exceeds the number of conditions or requirements or, otherwise, there are too many requirements for too few parameters to design. Such under- or over-defined tasks are sometimes not possible to solve using a direct approach. The number of solutions to such problems is multiple, and it is most rational to search for the optimal one by numerical methods since the more unknown design parameters there are to be designed, the more potential solutions there are. This article discusses a way to find an optimal solution to such an underdetermined problem by heuristic optimization methods on the basis of the example of designing a composite wing skin of an aircraft. Several heuristic approaches, specifically gradient descent and Tabu search, are studied to solve the design problem and to locate an optimal solution. They are also compared to a conventional direct approach. The examined composite lamina is optimized by the target function of minimum weight with the constraints of strength and buckling failure criteria. In most of the observed cases, the heuristic method designed structures which were considerably better than the structures that were obtained by conventional direct approaches in terms of the weight to load ratio.

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Section: Resultsmentioning

confidence: 99%

Composite Lamina Model Design with the Use of Heuristic Optimization

2023

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“…The present article is a logical continuation of our previous study [12] on scheduling in the case of multi-objective production process with the use of heuristic optimisation. This study is aimed to illustrate the significance of considering real-time observation on machines sustainability and interoperating this data in scheduling system.…”

Section: Research Goals and Aims Of The Present Articlementioning

confidence: 94%

“…Among the widely used are: genetic algorithm (GA) [7] and Tabu Search (TS) [24]. Papers comparing TS and GA algorithms for selected issues [12,25] agree that both of them are suitable for production scheduling optimization problems and it is impossible to unequivocally indicate the better one. For the considered problem of a decision-making process in production scheduling, GA and TS algorithms were chosen to use and additional Neuro-Tabu Search (NTS) uniting in itself TS with neural network was taken under consideration.…”

Section: Selected Algorithmsmentioning

confidence: 99%

“…As it was mentioned, the study of present article is based on our previous research [12], where implementation of Tabu Search and genetic algorithm were observed with the same initial historical company data to present research. Results obtained are published in the mentioned article and could be briefly interpreted as moderate success of both algorithms.…”

Section: Genetic Algorithm and Tabu Searchmentioning

confidence: 99%

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Bulletin of the Polish Academy of Sciences: Technical Sciences

Burduk,

Musiał,

Balashov

et al. 2022

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The paper deals with the issue of production scheduling for various types of employees in a large manufacturing company where the decision-making process was based on a human factor and the foreman's know-how, which was error-prone. Modern production processes are getting more and more complex. A company that wants to be competitive on the market must consider many factors. Relying only on human factors is not efficient at all. The presented work has the objective of developing a new employee scheduling system that might be considered a particular case of the job shop problem from the set of the employee scheduling problems. The Neuro-Tabu Search algorithm and the data gathered by manufacturing sensors and process controls are used to remotely inspect machine condition and sustainability as well as for preventive maintenance. They were used to build production schedules. The construction of the Neuro-Tabu Search algorithm combines the Tabu Search algorithm, one of the most effective methods of constructing heuristic algorithms for scheduling problems, and a self-organizing neural network that further improves the prohibition mechanism of the Tabu Search algorithm. Additionally, in the paper, sustainability with the use of Industry 4.0 is considered. That would make it possible to minimize the costs of employees' work and the cost of the overall production process. Solving the optimization problem offered by Neuro-Tabu Search algorithm and real-time data shows a new way of production management.

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Solving Scheduling Problems in Case of Multi-objective Production Using Heuristic Optimization

Cited by 2 publications

References 15 publications

Composite Lamina Model Design with the Use of Heuristic Optimization

Composite Lamina Model Design with the Use of Heuristic Optimization

Bulletin of the Polish Academy of Sciences: Technical Sciences

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