Search results for: Sujin Bureerat

Items from 1 to 20 out of 25 results

article

A new chaotic Lévy flight distribution optimization algorithm for solving constrained engineering problems

Betül Sultan Yıldız, Sumit Kumar, Nantiwat Pholdee, Sujin Bureerat, more

This work proposed a new metaheuristic dubbed as Chaotic Lévy flight distribution (CLFD) algorithm, to address physical world engineering optimization problems that incorporate the chaotic maps in the elementary Lévy flight distribution (LFD). Hybridization aims to increase the LFD rate of convergence while also providing a problem‐free optimization approach. The proposed methodology is investigated...

article

Robust design of a robot gripper mechanism using new hybrid grasshopper optimization algorithm

Betül Sultan Yildiz, Nantiwat Pholdee, Sujin Bureerat, Ali Riza Yildiz, more

Expert Systems > 38 > 3 > n/a - n/a

Structural design and optimization are important topics for the control and design of industrial robots. The motivation behind this research is to design a robot gripper mechanism. To explore robust design of the robot gripper mechanism, a new optimization approach based on a grasshopper optimization algorithm and Nelder–Mead algorithm is developed for requiring a fast and accurate solution. Additionally,...

article

A novel hybridized metaheuristic technique in enhancing the diagnosis of cross‐sectional dent damaged offshore platform members

Wonsiri Punurai, Md Samdani Azad, Nantiwat Pholdee, Sujin Bureerat, more

Computational Intelligence > 36 > 1 > 132 - 150

Offshore jacket platforms are widely used for oil and gas extraction as well as transportation in shallow to moderate water depth. Tubular cross‐sectional elements are used to construct offshore platforms. Tubular cross sections impart higher resistance against hydrodynamic forces and have high torsional rigidity. During operation, the members can be partially or fully damaged due to lateral impacts...

article

A novel self-adaptive hybrid multi-objective meta-heuristic for reliability design of trusses with simultaneous topology, shape and sizing optimisation design variables

Natee Panagant, Sujin Bureerat, Kang Tai

Structural and Multidisciplinary Optimization > 2019 > 60 > 5 > 1937-1955

Performing the design of a truss including topological, shape and sizing (TSS) variables simultaneously is a challenging but important task for a designer. It is even more interesting when the design problem involves random parameters. In this paper, a novel hybrid meta-heuristic based on the whale optimisation algorithm (WOA) and success history–based adaptive differential evolution (SHADE) is developed...

article

Simultaneous topology, shape, and size optimization of trusses, taking account of uncertainties using multi-objective evolutionary algorithms

Teerapol Techasen, Kittinan Wansasueb, Natee Panagant, Nantiwat Pholdee, more

Engineering with Computers > 2019 > 35 > 2 > 721-740

This paper proposes the design of trusses using simultaneous topology, shape, and size design variables and reliability optimization. Objective functions consist of structural mass and reliability, while the probability of failure is set as a design constraint. Design variables are treated to simultaneously determine structural topology, shape, and sizes. Six test problems are posed and solved by...

article

Topology optimization of truss subjected to static and dynamic constraints by integrating simulated annealing into passing vehicle search algorithms

Ghanshyam G. Tejani, Vimal J. Savsani, Sujin Bureerat, Vivek K. Patel, more

Engineering with Computers > 2019 > 35 > 2 > 499-517

Three modified versions of passing vehicle search (PVS) are proposed and tested on truss topology optimization with static and dynamic constraints. PVS works on the mechanism of passing a vehicle on a two-lane highway. The heuristic nature of PVS allows the search to jump into non-visited regions (exploration) and also permits a local search of visited regions (exploitation). First, the original PVS...

article

ADOSH: software with graphic user interface for analysis and design of truss structures

Natee Panagant, Sujin Bureerat

Asian Journal of Civil Engineering > 2018 > 19 > 3 > 273-286

In this article, Analysis and Design Optimization of truss Structures using meta-Heuristics (ADOSH) software for truss structural analysis and optimization has been developed to solve truss optimization problems with shape and sizing design variables. Graphical user interface (GUI) of the software is designed to simplify the work process of designers. The software was developed based on MATLAB programming...

article

Synthesis of multiple cross-section pin fin heat sinks using multiobjective evolutionary algorithms

Sanchai Ramphueiphad, Sujin Bureerat

International Journal of Heat and Mass Transfer > 2018 > 118 > C > 462-470

This paper demonstrates multiobjective optimization of a multi cross-section pin fin heat sink (MCSPFHS) for use in electronic devices. The design problem is assigned to optimize junction temperature and fan pumping power of the heat sink. Design variables are encoded to shape the fin geometry with several pin fin cross-sections. The heat sink is set to be side-inlet-side-outlet (SISO) while several...

article

Optimal reactive power dispatch problem using a two-archive multi-objective grey wolf optimizer

Kasem Nuaekaew, Pramin Artrit, Nantiwat Pholdee, Sujin Bureerat

Expert Systems with Applications > 2017 > 87 > C > 79-89

In this paper, a novel two-archive Multi-Objective Grey Wolf Optimizer (2ArchMGWO) is proposed for solving Multi-Objective Optimal Reactive Power Dispatch (MORPD) problems. The optimizer has been improved from its original Multi-Objective Grey Wolf Optimizer (MGWO) by modifying the reproduction operator and adding the 2-archive concept to the algorithm. It is then implemented on solving MORPD with...

article

A Comparative Study of Eighteen Self-adaptive Metaheuristic Algorithms for Truss Sizing Optimisation

Nantiwat Pholdee, Sujin Bureerat

KSCE Journal of Civil Engineering > 2018 > 22 > 8 > 2982-2993

Performance comparison of meta-heuristics (MHs) is conducted for truss sizing design. Six traditional truss sizing design problems with mass objective function subject to displacement and stress constraints were employed for performance test. The test problems have two types with and without including buckling constraints. Eighteen self-adaptive MHs from literature are employed to tackle the truss...

article

Optimal U-shaped baffle square-duct heat exchanger through surrogate-assisted self-adaptive differential evolution with neighbourhood search and weighted exploitation-exploration

Kittinan Wansaseub, Nantiwat Pholdee, Sujin Bureerat

Applied Thermal Engineering > 2017 > 118 > C > 455-463

In this paper, surrogate-assisted optimisation of a U-shaped baffle square-duct heat exchanger (USBSD-HX) is proposed. A single-objective design problem is formulated to optimise the heat exchanger thermal performance and friction loss. Several surrogate models including a Kriging model, radial basis function interpolation, a quadratic response surface model and support vector regression are used...

article

Two-stage surrogate assisted differential evolution for optimization of a non-circular drawing sequence

Nantiwat Pholdee, Sujin Bureerat, Hyun Moo Baek, Yong-Taek Im

International Journal of Precision Engineering and Manufacturing > 2017 > 18 > 4 > 567-573

In this work, a two-stage surrogate assisted optimization technique is proposed for optimizing a non-circular drawing (NCD) sequence. The objective function was introduced to minimize inhomogeneity of the effective strain distribution at the cross-sections of the drawn wire which could deteriorate its delamination characteristics. The design variables introduced were die geometry and reduction of...

chapter

Hybrid Population-Based Incremental Learning Using Real Codes

Sujin Bureerat

Lecture Notes in Computer Science > Learning and Intelligent Optimization > Main Track (Regular Papers) > 379-391

This paper proposes a hybrid evolutionary algorithm (EA) dealing with population-based incremental learning (PBIL) and some efficient local search strategies. A simple PBIL using real codes is developed. The evolutionary direction and approximate gradient operators are integrated to the main procedure of PBIL. The method is proposed for single objective global optimization. The search performance...

chapter

Improved Population-Based Incremental Learning in Continuous Spaces

Sujin Bureerat

Advances in Intelligent and Soft Computing > Soft Computing in Industrial Applications > Part I: Evolutionary Computation > 77-86

Population-based incremental learning (PBIL) is one of the well-established evolutionary algorithms (EAs). This method, although having outstanding search performance, has been somewhat overlooked compared to other popular EAs. Since the first version of PBIL, which is based on binary search space, several real code versions of PBIL have been introduced; nevertheless, they have been less popular than...

article

Optimization of flatness of strip during coiling process based on evolutionary algorithms

Nantiwat Pholdee, Sujin Bureerat, Won-Woong Park, Dong-Kyu Kim, more

International Journal of Precision Engineering and Manufacturing > 2015 > 16 > 7 > 1493-1499

In this paper, an optimization study was conducted for improving flatness of the strips during coiling process. The evolutionary optimizer coded by MATLAB is used for reducing axial inhomogeneity of the stress distribution and the maximum compressive stress calculated by Love’s elastic solution within a thin strip during the coiling process which might cause irregular surface profile of the strip...

article

Process optimization of a non-circular drawing sequence based on multi-surrogate assisted meta-heuristic algorithms

Nantiwat Pholdee, Hyun Moo Baek, Sujin Bureerat, Yong-Taek Im

Journal of Mechanical Science and Technology > 2015 > 29 > 8 > 3427-3436

Process optimization of a Non-circular drawing (NCD) sequence of a pearlitic steel wire was performed to improve the mechanical properties of a drawn wire based on surrogate assisted meta-heuristic algorithms. The objective function was introduced to minimize inhomogeneity of effective strain distribution at the cross-section of the drawn wire, which could deteriorate delamination characteristics...

article

Comparative performance of meta-heuristic algorithms for mass minimisation of trusses with dynamic constraints

Nantiwat Pholdee, Sujin Bureerat

Advances in Engineering Software > 2014 > 75 > Complete > 1-13

This paper investigates the search performances of various meta-heuristics (MHs) for solving truss mass minimisation with dynamic constraints. Several established MHs were used to solve five truss optimisation problems. The results obtained from using the various MHs were statistically compared based upon convergence rate and consistency. It was found that the best optimisers for this design task...

article

Simultaneous topology and sizing optimization of a water distribution network using a hybrid multiobjective evolutionary algorithm

Sujin Bureerat, Krit Sriworamas

Applied Soft Computing > 2013 > 13 > 8 > 3693-3702

This paper proposes a new direction for design optimization of a water distribution network (WDN). The new approach introduces an optimization process to the conceptual design stage of a WDN. The use of multiobjective evolutionary algorithms (MOEAs) for simultaneous topology and sizing design of piping networks is presented. The design problem includes both topological and sizing design variables...

article

Hybridisation of real-code population-based incremental learning and differential evolution for multiobjective design of trusses

Nantiwat Pholdee, Sujin Bureerat

Information Sciences > 2013 > 223 > Complete > 136-152

This paper proposes a hybrid evolutionary algorithm for multiobjective optimisation of trusses using real-code population-based incremental learning (RPBIL) to solve multiobjective design problems. Differential evolution (DE) operators are integrated into the main procedure of RPBIL leading to a hybrid algorithm. The newly developed optimiser, along with some established multiobjective evolutionary...

article

Performance enhancement of multiobjective evolutionary optimisers for truss design using an approximate gradient

Nantiwat Pholdee, Sujin Bureerat

Computers and Structures > 2012 > 106-107 > Complete > 115-124

This paper proposes hybridisation of evolutionary algorithms (EAs) and an efficient search strategy for truss optimisation. During an optimisation process, function gradients are approximated using already explored design solutions. The approximate gradient is then employed as a local search direction. The approximate gradient operator is integrated into the main search procedure of three multiobjective...

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INFONA - science communication portal

Search results for: Sujin Bureerat

A new chaotic Lévy flight distribution optimization algorithm for solving constrained engineering problems

Robust design of a robot gripper mechanism using new hybrid grasshopper optimization algorithm

A novel hybridized metaheuristic technique in enhancing the diagnosis of cross‐sectional dent damaged offshore platform members

A novel self-adaptive hybrid multi-objective meta-heuristic for reliability design of trusses with simultaneous topology, shape and sizing optimisation design variables

Simultaneous topology, shape, and size optimization of trusses, taking account of uncertainties using multi-objective evolutionary algorithms

Topology optimization of truss subjected to static and dynamic constraints by integrating simulated annealing into passing vehicle search algorithms

ADOSH: software with graphic user interface for analysis and design of truss structures

Synthesis of multiple cross-section pin fin heat sinks using multiobjective evolutionary algorithms

Optimal reactive power dispatch problem using a two-archive multi-objective grey wolf optimizer

A Comparative Study of Eighteen Self-adaptive Metaheuristic Algorithms for Truss Sizing Optimisation

Optimal U-shaped baffle square-duct heat exchanger through surrogate-assisted self-adaptive differential evolution with neighbourhood search and weighted exploitation-exploration

Two-stage surrogate assisted differential evolution for optimization of a non-circular drawing sequence

Hybrid Population-Based Incremental Learning Using Real Codes

Improved Population-Based Incremental Learning in Continuous Spaces

Optimization of flatness of strip during coiling process based on evolutionary algorithms

Process optimization of a non-circular drawing sequence based on multi-surrogate assisted meta-heuristic algorithms

Comparative performance of meta-heuristic algorithms for mass minimisation of trusses with dynamic constraints

Simultaneous topology and sizing optimization of a water distribution network using a hybrid multiobjective evolutionary algorithm

Hybridisation of real-code population-based incremental learning and differential evolution for multiobjective design of trusses

Performance enhancement of multiobjective evolutionary optimisers for truss design using an approximate gradient

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