Optimization of dynamic quantities of a four-bar mechanism using the Hybrid Cuckoo Search and Firefly Algorithm (H-CS-FA)

Bošković, Marina; Bulatović, Radovan R.; Šalinić, Slaviša; Miodragović, Goran; Bogdanović, Gordana

doi:10.1007/s00419-018-1457-8

Cited by 5 publications

(4 citation statements)

References 38 publications

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“…It is also possible to obtain the mass moments for each of the counterweights with respect to the local coordinate system origin, as shown in Equations ( 35) and (36).…”

Section: Counterweight Additionmentioning

confidence: 99%

“…Currently, the most popular optimization techniques for mechanical problems are based on metaheuristic methods: evolutionary [33], differential evolution [34], genetic [35], and Firefly [36] algorithms. These proposals were designed to find heuristics (i.e., partial solutions) that may provide sufficiently good tradeoffs for the dynamic balancing problem.…”

Section: Introductionmentioning

confidence: 99%

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Complete Balancing of the Six-Bar Mechanism Using Fully Cartesian Coordinates and Multiobjective Differential Evolution Optimization

et al. 2022

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The high-speed operation of unbalanced machines may cause vibrations that lead to noise, wear, and fatigue that will eventually limit their efficiency and operating life. To restrain such vibrations, a complete balancing must be performed. This paper presents the complete balancing optimization of a six-bar mechanism with the use of counterweights. A novel method based on fully Cartesian coordinates (FCC) is proposed to represent such a balanced mechanism. A multiobjective optimization problem was solved using the Differential Evolution (DE) algorithm to minimize the shaking force (ShF) and the shaking moment (ShM) and thus balance the system. The Pareto front is used to determine the best solutions according to three optimization criteria: only the ShF, only the ShM, and both the ShF and ShM. The dimensions of the counterweights are further fine-tuned with an analysis of their partial derivatives, volumes, and area–thickness relations. Numerical results show that the ShF and ShM can be reduced by 76.82% and 77.21%, respectively, when importance is given to either of them and by 45.69% and 46.81%, respectively, when equal importance is given to both. A comparison of these results with others previously reported in the literature shows that the use of FCC in conjunction with DE is a suitable methodology for the complete balancing of mechanisms.

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“…It is also possible to obtain the mass moments for each of the counterweights with respect to the local coordinate system origin, as shown in Equations ( 35) and (36).…”

Section: Counterweight Additionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Complete Balancing of the Six-Bar Mechanism Using Fully Cartesian Coordinates and Multiobjective Differential Evolution Optimization

et al. 2022

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“…The cyclic algorithm of the bat family (Loop BFA) represents a modification of the standard BA by including the loop search in the zone of solutions [2,19]. H-CS-FA represents a combination of two algorithms and it was used in the optimization of the dynamic quantities of the mechanism which is described in detail in [3,4]. Modified krill herd algorithm (MKH) proposed by Bulatović et al [5] corresponds to an improved version of the standard krill herd algorithm.…”

Section: Introductionmentioning

confidence: 99%

The application of metaheuristic algorithms in multi-objective optimization of engineering problems

Miodragović¹,

Bošković²,

Bulatović³

2022

Engineering Today

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Comparative testing of three modified metaheuristic algorithms - the cyclic algorithm of the bat family (Loop BFA), the hybrid cuckoo search and the firefly algorithm (H-CS-FA) and the modified krill herd algorithm (MKH)was performed in the paper. The authors tested these algorithms in relation to original ones and the effectiveness of the modifications was confirmed for each individual algorithm. Here, the effectiveness of all three algorithms was verified on two engineering problems in the field of metal cutting - optimization of the body of the turning knife and optimization of the eccentric of the clamping tool. In both cases, multi-objective optimization with two objective functions was performed. By comparing the obtained optimization results as well as the speed of convergence, appropriate conclusions about the efficiency of the algorithms and recommendations for their application were made.

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“…Thus, these algorithms give the local solution near to start point. Moreover, nature-inspired optimization techniques such as the genetic algorithm (GA) (Chaudhary and Chaudhary, 2014b;Erkaya, 2013), particle swarm optimization (PSO) (Farmani et al, 2011), hybrid cuckoo search (Boškovi c et al, 2018) and multi-objective optimization using a game algorithm (Yang et al, 2019) based on the priori approach are applied to balance the mechanisms. But, these optimization techniques require specific parameters for their convergence.…”

Section: Introductionmentioning

confidence: 99%

Dynamic balancing of the cleaning unit used in agricultural thresher using a non-dominated sorting Jaya algorithm

Singh

Chaudhary

2020

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Purpose This paper aims to propose a dynamically balanced mechanism for cleaning unit used in agricultural thresher machine using a dynamically equivalent system of point masses. Design/methodology/approach The cleaning unit works on crank-rocker Grashof mechanism. This mechanism can be balanced by optimizing the inertial properties of each link. These properties are defined by the dynamic equivalent system of point masses. Parameters of these point masses define the shaking forces and moments. Hence, the multi-objective optimization problem with minimization of shaking forces and shaking moments is formulated by considering the point mass parameters as the design variables. The formulated optimization problem is solved using a posteriori approach-based algorithm i.e. the non-dominated sorting Jaya algorithm (NSJAYA) and a priori approach-based algorithms i.e. Jaya algorithm and genetic algorithm (GA) under suitable design constraints. Findings The mass, center of mass and inertias of each link are calculated using optimum design variables. These optimum parameters improve the dynamic performance of the cleaning unit. The optimal Pareto set for the balancing problem is measured and outlined in this paper. The designer can choose any solution from the set and balance any real planar mechanism. Originality/value The efficiency of the proposed approach is tested through the existing cleaning mechanism of the thresher machine. It is found that the NSJAYA is computationally more efficient than the GA and Jaya algorithm. ADAMS software is used for the simulation of the mechanism.

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Optimization of dynamic quantities of a four-bar mechanism using the Hybrid Cuckoo Search and Firefly Algorithm (H-CS-FA)

Cited by 5 publications

References 38 publications

Complete Balancing of the Six-Bar Mechanism Using Fully Cartesian Coordinates and Multiobjective Differential Evolution Optimization

Complete Balancing of the Six-Bar Mechanism Using Fully Cartesian Coordinates and Multiobjective Differential Evolution Optimization

The application of metaheuristic algorithms in multi-objective optimization of engineering problems

Dynamic balancing of the cleaning unit used in agricultural thresher using a non-dominated sorting Jaya algorithm

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