A fuzzy reinforced Jaya algorithm for solving mathematical and structural optimization problems

Mortazavi, Ali

doi:10.1007/s00500-023-09206-5

Cited by 7 publications

(1 citation statement)

References 31 publications

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“…These techniques have led to a decrease in the total amount of material used and generated waste. It is worth noting that the fuzzy logic method has proven to be highly effective in various engineering applications [11,12]. The use of fuzzy logic methods for rebar reduction has not been very common.…”

Section: Introductionmentioning

confidence: 99%

A novel special length rebar order approach based on AI optimization techniques for reduction of rebar cutting waste

Güvel,

Karataş

2023

JCEMI

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Reducing the amount of waste material in the construction industry is a crucial goal for sustainability worldwide. Cutting rebars to fit the lengths needed for a building generates significant rebar waste. This study aims to reduce rebar-cutting waste in construction projects. In addition to planning the cut lengths of the standard 12-meter rebar using optimization methods, the study intends to reduce rebar-cutting waste by producing rebars in different lengths based on order frequency. A combination of genetic algorithm, fuzzy logic system, and a new algorithm method optimizes the cutting process, resulting in a significant reduction of rebar waste. Unlike prior studies, this research proposes a unique cutting length order for the rebar list created after optimization, aiming to reduce rebar cutting waste below the optimized level. The results show that the reduction in the amount of rebar waste is satisfactory.

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Section: Introductionmentioning

confidence: 99%

A novel special length rebar order approach based on AI optimization techniques for reduction of rebar cutting waste

Güvel,

Karataş

2023

JCEMI

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A novel type-2 decision mechanism for dynamic parameter adaptation: theory and application in mathematical and structural problems

Mortazavi

2024

Neural Comput & Applic

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Metaheuristic algorithms are stochastic-based search techniques widely used for solving different types of optimization problems. These methods mostly adjust their search behavior using pre-defined search pattern(s) regardless of the current problem specifications. Therefore, integrating them with logical auxiliary modules can significantly enhance their search efficiency by enabling them to dynamically adapt their search behavior. The present study introduces a novel decision-making approach that employs interval type-2 fuzzy logic to balance the search behavior during optimization process. The proposed approach, designed as a stand-alone module with the flexibility to be integrated into various algorithms, is incorporated into the Interactive Search Algorithm. The developed reinforced technique is named Type-2 Fuzzy Interactive Search Algorithm. Performance of the proposed method is tested on different unconstrained mathematical functions and constrained structural and mechanical optimization problems. The attained results are compared with standard ISA method and seven other metaheuristic techniques through a suite of numerical and statistical evaluations. Drawing from the obtained results, the integration of the type-2 fuzzy decision module significantly enhances the algorithm's search capability. This improvement is evident in terms of stability, accuracy, and computational cost. It is worth noting that the employed comparative performance index for the proposed method indicates improvements of 3.38, 13.09, 16.61, and 27.23 percent compared to the best solution found by the selected methods for engineering problems.

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Simultaneous optimization of capacity and topology of seismic isolation systems in multi-story buildings using a fuzzy reinforced differential evolution method

Mortazavi,

Kandemir

2024

Advances in Engineering Software

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A fuzzy reinforced Jaya algorithm for solving mathematical and structural optimization problems

Cited by 7 publications

References 31 publications

A novel special length rebar order approach based on AI optimization techniques for reduction of rebar cutting waste

A novel special length rebar order approach based on AI optimization techniques for reduction of rebar cutting waste

A novel type-2 decision mechanism for dynamic parameter adaptation: theory and application in mathematical and structural problems

Simultaneous optimization of capacity and topology of seismic isolation systems in multi-story buildings using a fuzzy reinforced differential evolution method

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