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Working on the Structural Components of Evolutionary Approaches
(Science and Technology Publications, Lda, 2024-11-20) Tzanetos, Alexandros; Kůdela, Jakub
Several researchers have turned their attention to the structural components of Evolutionary Computation and Swarm Intelligence-oriented approaches. This direction offers various opportunities, such as developing automatic design and configuration frameworks and integrating operators and mechanisms addressing known limitations. This work lists recent operators and discusses promising mechanisms found in existing atureinspired approaches. It also discusses how these algorithmic components can be integrated into modular frameworks and how they can be assessed and benchmarked. The work aims to emphasize the importance of the research direction about nature-inspired mechanisms and operators in the Evolutionary Computation field.
Dynamic Reduction of Network Flow Optimization Problem: Case of Waste-to-Energy Infrastructure Planning in Czech Republic
(Elsevier, 2024-10-01) Pluskal, Jaroslav; Šomplák, Radovan; Kůdela, Jakub; Eryganov, Ivan
Nowadays, many sophisticated tools based on various mathematical approaches are used to support planning and strategic decision-making. In the field of waste management, allocation and location problems based mainly on the structure network flow problem are used with respect to infrastructure planning. Modern formulations of the problem allow the inclusion of integer and nonlinear constraints that reflect real-world operations. However, despite the advanced computational technology, such real-world problems are difficult to solve in adequate detail due to the large scale of the problem. Thus, the links in the system are simplified, but most often a transport network is aggregated. The individual nodes in the system may then represent areas with tens or hundreds of thousands of inhabitants, which does not provide sufficient insight for location tasks. This paper presents an approach to dynamically reduce the network with respect to selected points of interest. The selected areas are modeled in greater detail, while with increasing distance the entities are more aggregated into larger units. The approach is based on a transformation of the original network and subsequent cluster analysis, preferably using existing transport infrastructure. The presented approach provides the possibility of practical application of complex tools that are currently mostly theoretical due to high computational demands. The methodology is applied to a case study of Waste-to-Energy infrastructure planning, which needs to model a large area to fill a large capacity facility.
Machinability analysis of Albromet W130 copper alloy by WEDM
(Springer, 2024-10-05) Mouralová, Kateřina; Bednář, Josef; Beneš, Libor; Zahradníček, Radim; Fries, Jiří
The unconventional Wire Electrical Discharge Machining (WEDM) technology represents a vital manufacturing technology in different industrial branches, such as aviation, military, automotive or energy industry. The WEDM energy demand is considerable and it is, therefore, desirable to reduce the machining time by optimising the machining parameters. In the study, the chosen parameters were Pulse off time, Gap voltage, Discharge current, Pulse on time, and Wire feed. Another factor we investigated in our Box-Behnken design of experiment was the workpiece thickness. The cutting speed, topography, and surface morphology were analysed in the samples produced for the design of experiment. This investigation was carried out using electron microscopy. The chemical composition of individual spots was analysed as well. The samples were found not to have significant differences in the appearance of craters on the edge and in the centre. Similarly, there was no significant difference observed between thicknesses and different parameter settings. The surfaces also show a large number of small bubbles. There were, however, no cracks or other defects found, even in the cross-sections of all samples.
Social Distancing as p-Dispersion Problem
(IEEE, 2020-08-14) Kůdela, Jakub
The spread of COVID-19 and similar viruses poses new challenges for our society. There is a strong incentive towards safety measures that help to mitigate the outbreaks. Many countries have imposed social distancing measures that require a minimum distance between people in given places, such as schools, restaurants, shops, etc. This in turn creates complications for these places, as their function is to serve as many people as they were originally designed for. In this paper, we pose the problem of using the available space in a given place, such that the social distancing measures are satisfied, as a p-dispersion problem. We use recent algorithmic advancements, that were developed for the p-dispersion problem, and combine them with discretization schemes to find computationally attainable solutions to the p-dispersion problem and investigate the trade-off between the level of discretization and computational efforts on one side, and the value of the optimal solution on the other.
Chance-Constrained Optimization Formulation for Ship Conceptual Design: A Comparison of Metaheuristic Algorithms
(MDPI, 2023-11-03) Kůdela, Jakub
This paper presents a new chance-constrained optimization (CCO) formulation for the bulk carrier conceptual design. The CCO problem is modeled through the scenario design approach. We conducted extensive numerical experiments comparing the convergence of both canonical and state-of-the-art metaheuristic algorithms on the original and CCO formulations and showed that the CCO formulation is substantially more difficult to solve. The two best-performing methods were both found to be differential evolution-based algorithms. We then provide an analysis of the resulting solutions in terms of the dependence of the distribution functions of the unit transportation costs and annual cargo capacity of the ship design on the probability of violating the chance constraints.

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