1. The MINLP approach to topology, shape and discrete sizing optimization of trussesSimon Šilih, Zdravko Kravanja, Stojan Kravanja, 2022, original scientific article Abstract: The paper presents the Mixed-Integer Non-linear Programming (MINLP) approach to the
synthesis of trusses. The solution of continuous/discrete non-convex and non-linear optimization
problems is discussed with respect to the simultaneous topology, shape and discrete sizing optimization of trusses. A truss MINLP superstructure of different topology and design alternatives
has been generated, and a special MINLP model formulation for trusses has been developed. In the
optimization model, a mass objective function of the structure has been defined and subjected to
design, load and dimensioning constraints. The MINLP problems are solved using the Modified
Outer-Approximation/Equality-Relaxation (OA/ER) algorithm. Multi-level MINLP strategies are introduced to accelerate the convergence of the algorithm. The Modified Two-Phase and the Sequential
Two-Phase MINLP strategies are proposed in order to solve highly combinatorial topology, shape
and discrete sizing optimization problems. The importance of local buckling constraints on topology
optimization is also discussed. Some simple numerical examples are shown at the end of the paper to
demonstrate the suitability and efficiency of the proposed method.
Keywords: structural synthesis, topology optimization, discrete sizing optimization, mixed-integer non-linear programming, MINLP, modified OA/ER algorithm, multi-level MINLP strategies, steel structures, trusses
Published in DKUM: 11.03.2025; Views: 0; Downloads: 3
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2. Radiotherapy department supported by an optimization algorithm for scheduling patient appointmentsMarcela Chavez, Silvia Gonzalez, Ruiz Alvaro, Duflot Patrick, Nicolas Jansen, Izidor Mlakar, Umut Arioz, Valentino Šafran, Philippe Kolh, Van Gasteren Marteyn, 2025, original scientific article Abstract: Prompt administration of radiotherapy (RT) is one of the most effective treatments against cancer. Eachday, the radiotherapy departments of large hospitals must plan numerous irradiation sessions, con-sidering the availability of human and material resources, such as healthcare professionals and linearaccelerators. With the increasing number of patients suffering from different types of cancers, manuallyestablishing schedules following each patient’s treatment protocols has become an extremely difficultand time-consuming task. We propose an optimization algorithm that automatically schedules andgenerates patient appointments. The model can rearrange fixed appointments to accommodate urgentcases, enabling hospitals to schedule appointments more efficiently. It respects the different treatment Prompt administration of radiotherapy (RT) is one of the most effective treatments against cancer. Eachday, the radiotherapy departments of large hospitals must plan numerous irradiation sessions, con-sidering the availability of human and material resources, such as healthcare professionals and linearaccelerators. With the increasing number of patients suffering from different types of cancers, manuallyestablishing schedules following each patient’s treatment protocols has become an extremely difficultand time-consuming task. We propose an optimization algorithm that automatically schedules andgenerates patient appointments. The model can rearrange fixed appointments to accommodate urgentcases, enabling hospitals to schedule appointments more efficiently. It respects the different treatment.
Keywords: appointments, hospital management, optimization algorithm, patient satisfaction, planning, radiotherapy
Published in DKUM: 25.02.2025; Views: 0; Downloads: 8
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3. Optimization of embedded retaining walls under the effects of groundwater seepage using a reliability-based and partial factor design approachRok Varga, Bojan Žlender, Primož Jelušič, 2024, original scientific article Abstract: In this paper, a comparative analysis of the effects of groundwater, seepage and hydraulic heave on the optimal design of embedded retaining walls is carried out. The optimization model for an optimal retaining wall (ORW) minimizes the total length of the retaining wall considering design constraints. The model is extended to include the probability of failure as an additional constraint. This overcomes the limitations of the partial safety factor approach, which does not fully account for uncertainties in the soil. In contrast, the reliability-based design (RBD) approach integrates these uncertainties and enables an assessment of the impact of seepage and hydraulic heave on the reliability of the structure. A real-coded genetic algorithm was used to determine optimal designs for both optimization methods. The results of the case study show that the addition of seepage (groundwater flow) to the hydrostatic conditions has a modest effect on the embedment depth. The design based on partial safety factors, which takes seepage into account, leads to a slight increase in the embedment depth of 0.94% compared to a retaining wall design that only takes the hydrostatic conditions of the groundwater into account. When designing on the basis of probability failure, the percentage increase in embedment depth due to seepage is between 2.19% and 6.41%, depending on the target probability of failure. Furthermore, the hydraulic heave failure mechanism did not increase the required embedment depth of the retaining wall, which means that the failure mechanism of rotation near the base was decisive for the design.
Keywords: embedded retaining wall, reliability-based design, partial safety factor design, optimization, genetic algorithm
Published in DKUM: 10.12.2024; Views: 0; Downloads: 11
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4. Optimization of a circular planar spiral wireless power transfer coil using a genetic algorithmNataša Prosen, Jure Domajnko, 2024, original scientific article Abstract: Circular planar spiral coils are the most important parts of wireless power transfer systems. This paper presents the optimization of wireless power transfer coils used for wireless power transfer, which is a problem when designing wireless power transfer systems. A single transmitter coil transfers power to a single receiving side. The performance of the wireless power transfer system depends greatly on the size and shape of the wireless power transfer system. Therefore, the optimization of the coils is of the utmost importance. The main optimization parameter was the coupling coefficient between the transmitter and the receiver coil in the horizontally aligned and misaligned position. A genetic evolutionary algorithm was used to optimize the coil, according to the developed cost function. The algorithm was implemented using the MATLAB programming language. The constraints regarding the design of the coils are also presented for the problem to be analyzed correctly. The results obtained using the genetic algorithm were first verified using FEM simulations. The optimized coils were later fabricated and measured to confirm the theory.
Keywords: wireless power transfer, coil optimization, genetic algorithm, coupling coefficient measurement
Published in DKUM: 14.08.2024; Views: 77; Downloads: 9
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5. Sustainable design of circular reinforced concrete column sections via multi-objective optimizationPrimož Jelušič, Tomaž Žula, 2023, original scientific article Abstract: An optimization model for reinforced concrete circular columns based on the Eurocodes is presented. With the developed optimization model, which takes into account the exact distribution of the steel reinforcement, which is not the case when designing with conventional column design charts, an optimal design for the reinforced concrete cross section is determined. The optimization model uses discrete variables, which makes the results more suitable for actual construction practice and fully exploits the structural capacity of the structure. A parametric study of the applied axial load and bending moment was performed for material cost and CO2 emissions. The results based on a single objective function show that the optimal design of the reinforced concrete column cross section obtained for the material cost objective function contains a larger cross-sectional area of concrete and a smaller area of steel compared with the optimization results when CO2 emissions are determined as the objective function. However, the optimal solution in the case where the material cost was assigned as the objective function has much more reserve in axial load capacity than in the optimal design where CO2 was chosen as the objective function. In addition, the multi-objective optimization was performed to find a set of solutions that provide the best trade-offs between the material cost and CO2 emission objectives.
Keywords: reinforced concrete columns, circular cross section, costs, CO2 emissions, multi-objective optimization, genetic algorithm
Published in DKUM: 15.04.2024; Views: 338; Downloads: 216
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8. Indoor positioning system based on bluetooth low energy technology and a nature-inspired optimization algorithmPrimož Bencak, Darko Hercog, Tone Lerher, 2022, original scientific article Abstract: Warehousing is one of the most important activities in the supply chain, enabling competitive advantage. Effective management of warehousing processes is, therefore, crucial for achieving minimal costs, maximum efficiency, and overall customer satisfaction. Warehouse Management Systems (WMS) are the first steps towards organizing these processes; however, due to the human factor involved, information on products, vehicles and workers may be missing, corrupt, or misleading. In this paper, a cost-effective Indoor Positioning System (IPS) based on Bluetooth Low Energy (BLE) technology is presented for use in Intralogistics that works automatically, and therefore minimizes the possibility of acquiring incorrect data. The proposed IPS solution is intended to be used for supervising order-picker movements, movement of packages between workstations, and tracking other mobile devices in a manually operated warehouse. Only data that are accurate, reliable and represent the actual state of the system, are useful for detailed material flow analysis and optimization in Intralogistics. Using the developed solution, IPS technology is leveraged to enhance the manually operated warehouse operational efficiency in Intralogistics. Due to the hardware independence, the developed software solution can be used with virtually any BLE supported beacons and receivers. The results of IPS testing in laboratory/office settings show that up to 98% of passings are detected successfully with time delays between approach and detection of less than 0.5 s.
Keywords: warehousing, indoor positioning systems, bluetooth low energy, particle swarm optimization, nature–inspired algorithm, intralogistics
Published in DKUM: 17.08.2023; Views: 432; Downloads: 556
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9. An efficient metaheuristic algorithm for job shop scheduling in a dynamic environmentHankun Zhang, Borut Buchmeister, Xueyan Li, Robert Ojsteršek, 2023, original scientific article Keywords: metaheuristic algorithm, improved multi-phase particle swarm optimization, cellular neighbor network, dynamic job shop scheduling, simulation modelling
Published in DKUM: 19.05.2023; Views: 527; Downloads: 48
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10. Algorithmic linearization improves Syringe-based extrusion in elastic systems using Hydrogel-based materialsJernej Vajda, Luka Banović, Mihael Miško, Igor Drstvenšek, Marko Milojević, Uroš Maver, Boštjan Vihar, 2023, original scientific article Abstract: Accuracy and precision are essential in extrusion-based material handling such as three-dimensional (3D) bioprinting. However, the elasticity of components, backlash, variability of nozzle and cartridge shapes, etc. can lead to unpredictable printing results, which is further complicated by the wide range of rheologically diverse materials and complex sample designs. To address this issue, we present an algorithmic approach to compensate for the discrepancies between piston motion and material extrusion in syringe-based extrusion systems. This approach relies on cyclical, iterative optimization through rapid piston movements, which are adjusted based on extrusion analysis. In this work we establish a general theoretical framework for extrusion and link the rheological properties of prepared hydrogels with shear rates in a typical bioprinting process. The determined properties are compared with the success of the developed algorithm to modify machine instructions for precise material deposition of short, interrupted lines, as well as multi-layered scaffold structures. Overall, our approach provides a means of improving the accuracy and precision of complex extrusion-based bioprinting systems, without prior knowledge of set-up or material properties, making it highly versatile and suitable for a wide range of applications, particularly when the combined set-up and material properties are too complex for solely predictive approaches.
Keywords: 3D bioprinting, syringe extrusion, optimization, algorithm
Published in DKUM: 21.04.2023; Views: 684; Downloads: 110
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