Traditional cycloidal speed reducers (with two cycloid discs per one stage, mutually turned by an angle of 180°) are well known for their remarkable dynamic stability. This paper analyses dynamic behaviour of a two-stage cycloidal speed...

This research aims to show the effects of adding cardinality constraints to limit the number of different cross-sections used in simultaneous sizing and shape optimization of truss structures. The optimal solutions for sizing and shape optimized trusses result in a generally high, and impractical, number of different cross-sections being used. This paper presents the influence of constraining the number of different cross-sections used on the optimal results to bring the scientific results closer to the applicable results. The savings achieved using the cardinality constraint are expected to manifest in more than just the minimization of weight but in all the other aspects of truss construction, such as labor, assembly time, total weld length, surface area to be treated, transport, logistics, and so on. It is expected that the optimal weight of the structures would be greater than when not using this constraint; however, it would still be below conventionally sized structures and have the added benefits derived from the simplicity and elegance of the solution. The results of standard test examples for each different cardinality constraint value are shown and compared to the same examples using only a single cross-section on all bars and the overall optimal solution, which does not have the cardinality constraint. An additional comparison is made with results of just the sizing optimization from previously published research where authors first used the same cardinality constraint.

This article aims to demonstrate the difference in results for minimal weight optimization for a 17 bar truss sizing and shape optimization problem. In order to attain results which can be produced in practice Euler bucking, minimal element length, maximal stress and maximal displacement constraints were used. Using the same initial setup, optimization was conducted using particle swarm optimization algorithm and compared to genetic algorithm. Optimal results for both algorithms are compared to initial values which are analytically calculated. The individual element lengths are observed, along with the overall weight, surface area and included number of different cross-sections.

The influence of cardinality constraints on the simultaneous optimization of truss sizing, shape, and topology, when used for weight minimization, is explored in this study. By integrating precise cardinality constraints, the implications for achieving global optimal solutions for different numbers of different cross-sections were investigated. This research underscores the significance of these constraints in enhancing the practical applicability of optimization outcomes, particularly in complex structural configurations where traditional approaches may lead to excessive requirements of numerous different cross-sections. Comprehensive experimentation and comparative analysis, across various standard and practical truss examples, demonstrate the effectiveness of cardinality constraints in guiding optimal design configurations. Notably, the presented findings reveal a trend in weight savings, depending on the number of different cross-sections used relative to global optima, displaying the utility of this constraint in achieving practical and efficient designs. Case studies on a produced roof truss underscore the applicability of this approach in practical engineering scenarios. They offer insights into the optimal design configurations for problems that do not allow for drastic changes due to their restrictive design mandate. This research is part of continued advancements in truss optimization methodologies, with implications for promoting sustainability and cost-effectiveness in structural engineering practice. By elucidating the role of cardinality constraints in shaping the optimal design solutions, this study should contribute to the broader discourse on efficient structural design strategies.

Ovaj rad predstavlja nastavak istraživanja grupe autora u oblasti optimizacije efikasnosti toplotnih prijemnika sunčeve energije (u daljem tekstu: PSE). Dosadašnji rad se zasnivao na metodi optimizacije poznatoj kao metoda slučajne pretrage, kao jedne od najstarijih heurističkih optimizacionih metoda. U radu su rezultati prethodnih istraživanja upoređeni sa rezultatima dobijenim novom metodom optimizacije koja se naziva teaching-learning based optimization – TLBO. Predstavljen je način funkcionisanja ove metode, kao njena primena na optimizaciju toplotnih PSE-a. Za potrebe ovog rada unapređen je dosadašnji matematički model, kako bi u optimizaciju bio uključen što veći broj promenljivih koje imaju uticaja kako na proizvodnju tako i na cenu PSE-a. U obzir su uzeti prijemnici sa cevima kvadratnog poprečnog preseka, kao i prijemnici sa cevim okruglog poprečnog preseka. Izvedeni su zaključci i data je uporedna analiza rezultata dobijenih metodom slučajne pretrage i metodom TLBO.