Use of a Simulation Environment and Metaheuristic Algorithm for Human Resource Management in a Cyber-Physical System

Zhang, Hankun; Buchmeister, Borut; Liu, Shifeng; Ojsteršek, Robert

doi:10.1007/978-3-030-04137-3_14

Cited by 5 publications

(4 citation statements)

References 35 publications

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“…Due to its very strong convergence, the HKA can easily fall into the local minimum [18,21]. Therefore, the HKA needs to be improved.…”

Section: Improved Heuristic Kalman Algorithmmentioning

confidence: 99%

“…In the IHKA, a function is introduced that handles the boundary constraint after the solutions are generated by the Gaussian distribution, then the best position of each individual is stored and updated after the evaluation process of the generated solutions, and, finally, the cellular neighbor network is introduced during the measurement process to select the best samples under consideration. The general pseudo-code of the IHKA is shown in Algorithm 1 and the flowchart of the IHKA is shows in Figure 3 [21]. atics 2021, 9, 909 6 of 23…”

Section: Improved Heuristic Kalman Algorithmmentioning

confidence: 99%

“…In this paper, the MaxIter of the IHKA and HKA was set according to a large number of preliminary experiments, and the others were set according to the previous literature. The parameters r, c, k, N, N ξ and α were set according to [18,21]. The parameters p and d were set according to [22] and [26], respectively.…”

Section: Defining the Parametersmentioning

confidence: 99%

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Advanced Metaheuristic Method for Decision-Making in a Dynamic Job Shop Scheduling Environment

Zhang

Buchmeister

et al. 2021

Mathematics

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As a well-known NP-hard problem, the dynamic job shop scheduling problem has significant practical value, so this paper proposes an Improved Heuristic Kalman Algorithm to solve this problem. In Improved Heuristic Kalman Algorithm, the cellular neighbor network is introduced, together with the boundary handling function, and the best position of each individual is recorded for constructing the cellular neighbor network. The encoding method is introduced based on the relative position index so that the Improved Heuristic Kalman Algorithm can be applied to solve the dynamic job shop scheduling problem. Solving the benchmark example of dynamic job shop scheduling problem and comparing it with the original Heuristic Kalman Algorithm and Genetic Algorithm-Mixed, the results show that Improved Heuristic Kalman Algorithm is effective for solving the dynamic job shop scheduling problem. The convergence rate of the Improved Heuristic Kalman Algorithm is reduced significantly, which is beneficial to avoid the algorithm from falling into the local optimum. For all 15 benchmark instances, Improved Heuristic Kalman Algorithm and Heuristic Kalman Algorithm have obtained the best solution obtained by Genetic Algorithm-Mixed. Moreover, for 9 out of 15 benchmark instances, they achieved significantly better solutions than Genetic Algorithm-Mixed. They have better robustness and reasonable running time (less than 30 s even for large size problems), which means that they are very suitable for solving the dynamic job shop scheduling problem. According to the dynamic job shop scheduling problem applicability, the integration-communication protocol was presented, which enables the transfer and use of the Improved Heuristic Kalman Algorithm optimization results in the conventional Simio simulation environment. The results of the integration-communication protocol proved the numerical and graphical matching of the optimization results and, thus, the correctness of the data transfer, ensuring high-level usability of the decision-making method in a real-world environment.

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“…Due to its very strong convergence, the HKA can easily fall into the local minimum [18,21]. Therefore, the HKA needs to be improved.…”

Section: Improved Heuristic Kalman Algorithmmentioning

confidence: 99%

Section: Improved Heuristic Kalman Algorithmmentioning

confidence: 99%

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Advanced Metaheuristic Method for Decision-Making in a Dynamic Job Shop Scheduling Environment

Zhang

Buchmeister

et al. 2021

Mathematics

Self Cite

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“…In the time of Industry 4.0, where the high complexity of manufacturing systems is reflected in multi-criteria optimization problems that must be solved while improving the productivity and sustainability of the production system. Personalized products in Industry 4.0 manufacturing systems are represented by the high-mix low-volume production type [1]. Adequate evaluation of the cost-time diagram for the high-mix low-volume production type is not capable of describing fully the effects of multi-criteria optimization on a specified production type [2].…”

Section: Introductionmentioning

confidence: 99%

The Impact of Manufacturing Flexibility and Multi-Criteria Optimization on the Sustainability of Manufacturing Systems

Ojsteršek

Buchmeister

2020

Symmetry

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The presented manuscript deals with the impact of manufacturing flexibility on cost-time investment as a function of sustainable production, which addresses the company’s sustainable social and environmental impact adequately. The impact of manufacturing flexibility on cost-time investment in the research sphere is not described, despite the fact that we know its key role in the high-mix low-volume production types. Recently, researchers have been addressing intensively the impacts of various parameters on the sustainable aspect and its dependence on manufacturing flexibility. The complexity of the influence parameters is reflected in the multi-criteria nature of optimization problems that can be solved with appropriate use of the evolutionary computation methods. The manuscript presents a new method of manufacturing flexibility modelling, with respect to the four-level architectural model, which reflected as a symmetry phenomena influence on the cost-time profile diagram. The solution to a complex optimization problem is derived using the proposed improved heuristic Kalman algorithm method. A new method is presented of optimization parameters’ evaluation with respect to the manufacturing flexibility impacts on cost-time investment. The large impact of appropriate multi-criteria optimization on a sustainably justified production system is presented, with the experimental work on benchmark datasets and an application case. The new method allows a comprehensive optimization approach, and validation of the optimization results by which we can provide more sustainable products, manufacturing processes, and increase the company’s total, social and environmental benefits.

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Metaheuristic algorithms and their applications in performance optimization of cyber-physical systems having applications in logistics

Saini,

Maan,

Kumar

et al. 2024

Int J Syst Assur Eng Manag

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Use of a Simulation Environment and Metaheuristic Algorithm for Human Resource Management in a Cyber-Physical System

Cited by 5 publications

References 35 publications

Advanced Metaheuristic Method for Decision-Making in a Dynamic Job Shop Scheduling Environment

Advanced Metaheuristic Method for Decision-Making in a Dynamic Job Shop Scheduling Environment

The Impact of Manufacturing Flexibility and Multi-Criteria Optimization on the Sustainability of Manufacturing Systems

Metaheuristic algorithms and their applications in performance optimization of cyber-physical systems having applications in logistics

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