Minimum-time motion planning for a robot arm using the Bees Algorithm

Ang, Mei Choo; Pham, Duc Truong; Ng, Kok Weng

doi:10.1109/indin.2009.5195852

Cited by 11 publications

(6 citation statements)

References 7 publications

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“…The application of Bees Algorithm has been successful in solving problems of continuous type 34 to the combinatorial type 36 including multi-objective optimisation problems. 37,38 In addition to that, these applications also showed that the Bees Algorithm produced better results than those generated from EAs and other algorithms. 12,33,39,40 The strength and the advantages of the Bees Algorithm based on the findings from these literature showed that the Bees Algorithm is an intriguing algorithm that deserved to be further explored.…”

Section: Bees Algorithmmentioning

confidence: 89%

Combining the Bees Algorithm and shape grammar to generate branded product concepts

Ang

Pham

2013

Proceedings of the Institution of Mechanical Engineers, Part B:

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Generating product design concepts to meet functional requirements while maintaining a specific brand identity is a daunting task for a designer. Shape grammars have been applied to describe the creation of branded product shapes via a set of shape rules and were manually used to create a family of new design concepts, which maintain the product brand identity. Nevertheless, shape grammars are not able to evaluate whether the generated new product concepts can fulfil specified functional requirements of a product. In this research work, shape grammar is combined with an optimisation technique known as the Bees Algorithm to derive a computational architecture for generating branded design concepts that can meet a specified functional requirement. This combination approach allows shape rules to evolve while evaluating how well the outcomes of the new design concepts meet a specified functional requirement. This paper describes how the combination of the Bees Algorithm with shape grammar is created to generate branded product concepts, and shows that this approach can outperform a combination of shape grammar with an evolutionary algorithm.

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Section: Bees Algorithmmentioning

confidence: 89%

Combining the Bees Algorithm and shape grammar to generate branded product concepts

Ang

Pham

2013

Proceedings of the Institution of Mechanical Engineers, Part B:

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“…Ang et al 13 proposed a Pareto-based multiobjective BA to determine the minimum traveling time for a robot arm, taking into consideration the smoothness of trajectory. In the BA model, the artificial bees have a similar communication medium to bias the search in the search space.…”

Section: Bee-inspired Algorithmsmentioning

confidence: 99%

“…Some recent studies on the BA model are available in the literature as follows. Ang et al proposed a Pareto‐based multiobjective BA to determine the minimum traveling time for a robot arm, taking into consideration the smoothness of trajectory. Sagheer et al presented an improved scatter search algorithm based on the BA model and evaluated the proposed algorithm using TSP.…”

Section: Related Workmentioning

confidence: 99%

A dynamic fuzzy‐based dance mechanism for the bee colony optimization algorithm

Choong

Wong

Lim

2018

Computational Intelligence

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The bee colony optimization (BCO) algorithm with a linear dance function (denoted as the BCO-Linear algorithm) is inspired by the bees' foraging behaviors, in which waggle dances are modeled as a communication medium among bees. Through these informative waggle dances, more bees are recruited toward exploring more profitable search regions. In the BCO-Linear algorithm, a fitter bee is allowed to dance longer, and the dance duration is determined by a linear function with a scaling parameter that requires manual tuning. This article presents a dynamic fuzzy-based dance mechanism, ie, the BCO-Fuzzy algorithm, to solve the manual tuning problem. A fuzzy-based approach is applied to regulate the duration of waggle dances instead of regulating the dance duration using a linear function.The proposed BCO-Fuzzy algorithm comprises parameters that are dynamically controlled based on the feedback of the search process, therefore overcoming the limitation of manual parameter tuning of the BCO-Linear algorithm. The BCO-Fuzzy algorithm is evaluated comprehensively using a set of benchmark traveling salesman problems. The experimental results show that the performance of the BCO-Fuzzy algorithm is comparable with that of the BCO-Linear algorithm. Specifically, the dynamic fuzzy-based dance mechanism improves the BCO algorithm in terms of rewarding dance instances near the inflection point. Performance comparison with other Computational Intelligence. 2018;34:999-1024. wileyonlinelibrary.com/journal/coin

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“…The algorithm has been shown to be able to solve multiobjective optimisation problems [4,7]. Pham et al [5] has applied the Bees Algorithm with basic operators on the PCB assembly problem with MBTD successfully in 2007.…”

Section: Bees Algorithmmentioning

confidence: 99%

PCB assembly optimisation using the Bees Algorithm enhanced with TRIZ operators

Mei

Pham

Anthony

et al. 2010

IECON 2010 - 36th Annual Conference on IEEE Industrial Electronics Society

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This paper describes an application of the Bees Algorithm with new operators inspired by the TRIZ methodology to optimise assembly sequences for a printedcircuit board (PCB) assembly machine. The specific problem investigated is the assembly of PCBs using a machine of the moving-board-with-time-delay type. The results obtained using the Bees Algorithm with the TRIZ-inspired operators are found to be better than those by other algorithms from the literature including the original Bees Algorithm.I.

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Minimum-time motion planning for a robot arm using the Bees Algorithm

Cited by 11 publications

References 7 publications

Combining the Bees Algorithm and shape grammar to generate branded product concepts

Combining the Bees Algorithm and shape grammar to generate branded product concepts

A dynamic fuzzy‐based dance mechanism for the bee colony optimization algorithm

PCB assembly optimisation using the Bees Algorithm enhanced with TRIZ operators

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