Optimum synthesis of a four-bar mechanism using the modified bacterial foraging algorithm

Mezura-Montes, Efrén; Portilla-Flores, Edgar Alfredo; Hernández-Ocaña, Betania

doi:10.1080/00207721.2012.745023

Cited by 24 publications

(8 citation statements)

References 26 publications

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“…MBFOA, originally proposed in [13] and extended in [19,20], is based on the original BFOA [23] but it is focused on solving CNOPs. A set of feasibility rules proposed by Deb [2] is adopted in MBFOA as the constraint-handling mechanism, employed as selection criteria when bacteria are compared: (1) between two feasible bacteria, the one with the best objective function value is chosen, (2) between one feasible bacterium and another infeasible one, the feasible is chosen, and (3) between two infeasible bacteria, the one with the lowest sum of constraint violation is chosen.…”

Section: Modified Bacterial Foraging Op-timization Algorithm (Mbfoa)mentioning

confidence: 99%

Stepsize control on the modified bacterial foraging algorithm for constrained numerical optimization

Hernández-Ocaña

Pozos-Parra

Mezura-Montes

2014

Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation

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The stepsize value is one of the most sensitive parameters in the bacterial foraging optimization algorithm when solving constrained numerical optimization problems. In this paper, four stepsize control mechanisms are proposed and analyzed in the modified bacterial foraging optimization algorithm. The first one is based on a random value which remains fixed during the search, the second one generates a random value per cycle, the third one is based on a nonlinear decreasing function and the last one is an adaptive approach. Seven experiments are proposed to evaluate the abilities of each mechanism to: (1) obtain competitive final results, (2) find feasible solutions, (3) find the feasible global optimum, (4) promote successful swims, and (5) decrease the constraint violation. A comparison against two state-of-theart algorithms is considered to evaluate the performance of the most competitive control mechanism. A well-known set of constrained numerical optimization problems is used in the experiments as well as six performance measures. The results obtained show that the control mechanism based on the nonlinear decreasing function is the most competitive and provides the ability to generate better solutions late in the search.

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Section: Modified Bacterial Foraging Op-timization Algorithm (Mbfoa)mentioning

confidence: 99%

Stepsize control on the modified bacterial foraging algorithm for constrained numerical optimization

Hernández-Ocaña

Pozos-Parra

Mezura-Montes

2014

Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation

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“…The design optimization problem in Mezura-Montes et al, (2014) was formulated in two forms (singleobjective and bi-objective). The authors then restructured the conventional BFA for multiobjective optimization.…”

Section: Introductionmentioning

confidence: 99%

Multiobjective Optimization of Solar-Powered Irrigation System with Fuzzy Type-2 Noise Modelling

Ganesan

Vasant

Elamvazuthi

2017

Emerging Research on Applied Fuzzy Sets and Intuitionistic Fuzzy Matrices

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“…Moreover, MBFOA was simplified and improved in its step size handling in the swim operator in [ 29 ]. Further modifications were proposed in [ 30 , 31 ] to solve multiobjective CNOPs, where some four-bar mechanisms were tackled. More recently, MBFOA was further improved to solve CNOPs in the so-called Improved MBFOA (IMBFOA for short) [ 32 ] where the idea of two-swim movements within the chemotaxis process was initially explored.…”

Section: Introductionmentioning

confidence: 99%

Two-Swim Operators in the Modified Bacterial Foraging Algorithm for the Optimal Synthesis of Four-Bar Mechanisms

Hernández-Ocaña

Pozos-Parra

Mezura-Montes

et al. 2016

Computational Intelligence and Neuroscience

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This paper presents two-swim operators to be added to the chemotaxis process of the modified bacterial foraging optimization algorithm to solve three instances of the synthesis of four-bar planar mechanisms. One swim favors exploration while the second one promotes fine movements in the neighborhood of each bacterium. The combined effect of the new operators looks to increase the production of better solutions during the search. As a consequence, the ability of the algorithm to escape from local optimum solutions is enhanced. The algorithm is tested through four experiments and its results are compared against two BFOA-based algorithms and also against a differential evolution algorithm designed for mechanical design problems. The overall results indicate that the proposed algorithm outperforms other BFOA-based approaches and finds highly competitive mechanisms, with a single set of parameter values and with less evaluations in the first synthesis problem, with respect to those mechanisms obtained by the differential evolution algorithm, which needed a parameter fine-tuning process for each optimization problem.

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Optimum synthesis of a four-bar mechanism using the modified bacterial foraging algorithm

Cited by 24 publications

References 26 publications

Stepsize control on the modified bacterial foraging algorithm for constrained numerical optimization

Stepsize control on the modified bacterial foraging algorithm for constrained numerical optimization

Multiobjective Optimization of Solar-Powered Irrigation System with Fuzzy Type-2 Noise Modelling

Two-Swim Operators in the Modified Bacterial Foraging Algorithm for the Optimal Synthesis of Four-Bar Mechanisms

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