An enhancement to the Bees Algorithm with slope angle computation and Hill Climbing Algorithm and its applications on scheduling and continuous-type optimisation problem. / Yuce, Baris; Pham, Duc Truong; Packianather, Michael S.; Mastrocinque, Ernesto.

In: Production and Manufacturing Research, Vol. 3, No. 1, 12.01.2015, p. 3-19.

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An enhancement to the Bees Algorithm with slope angle computation and Hill Climbing Algorithm and its applications on scheduling and continuous-type optimisation problem. / Yuce, Baris; Pham, Duc Truong; Packianather, Michael S.; Mastrocinque, Ernesto.

In: Production and Manufacturing Research, Vol. 3, No. 1, 12.01.2015, p. 3-19.

Research output: Contribution to journalArticlepeer-review

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Yuce, Baris ; Pham, Duc Truong ; Packianather, Michael S. ; Mastrocinque, Ernesto. / An enhancement to the Bees Algorithm with slope angle computation and Hill Climbing Algorithm and its applications on scheduling and continuous-type optimisation problem. In: Production and Manufacturing Research. 2015 ; Vol. 3, No. 1. pp. 3-19.

BibTeX

@article{74c11e33d7d64c908126966f94b3e861,
title = "An enhancement to the Bees Algorithm with slope angle computation and Hill Climbing Algorithm and its applications on scheduling and continuous-type optimisation problem",
abstract = "This paper focuses on improvements to the Bees Algorithm (BA) with slope angle computation and Hill Climbing Algorithm (SACHCA) during the local search process. First, the SAC was employed to determine the inclination of the current sites. Second, according to the slope angle, the HCA was utilised to guide the algorithm to converge to the local optima. This enabled the global optimum of the given problem to be found faster and more precisely by focusing on finding the available local optima first before turning the attention on the global optimum. The proposed enhancements to the BA have been tested on continuous-type benchmark functions and compared with other optimisation techniques. The results show that the proposed algorithm performed better than other algorithms on most of the benchmark functions. The enhanced BA performs better than the basic BA, in particular on higher dimensional and complex optimisation problems. Finally, the proposed algorithm has been used to solve the single machine scheduling problem and the results show that the proposed SAC and HCA-BA outperformed the basic BA in almost all the considered instances, in particular when the complexity of the problem increases.",
author = "Baris Yuce and Pham, {Duc Truong} and Packianather, {Michael S.} and Ernesto Mastrocinque",
year = "2015",
month = jan,
day = "12",
doi = "10.1080/21693277.2014.976321",
language = "English",
volume = "3",
pages = "3--19",
journal = "Production and Manufacturing Research",
issn = "2169-3277",
publisher = "Taylor and Francis Ltd.",
number = "1",

}

RIS

TY - JOUR

T1 - An enhancement to the Bees Algorithm with slope angle computation and Hill Climbing Algorithm and its applications on scheduling and continuous-type optimisation problem

AU - Yuce, Baris

AU - Pham, Duc Truong

AU - Packianather, Michael S.

AU - Mastrocinque, Ernesto

PY - 2015/1/12

Y1 - 2015/1/12

N2 - This paper focuses on improvements to the Bees Algorithm (BA) with slope angle computation and Hill Climbing Algorithm (SACHCA) during the local search process. First, the SAC was employed to determine the inclination of the current sites. Second, according to the slope angle, the HCA was utilised to guide the algorithm to converge to the local optima. This enabled the global optimum of the given problem to be found faster and more precisely by focusing on finding the available local optima first before turning the attention on the global optimum. The proposed enhancements to the BA have been tested on continuous-type benchmark functions and compared with other optimisation techniques. The results show that the proposed algorithm performed better than other algorithms on most of the benchmark functions. The enhanced BA performs better than the basic BA, in particular on higher dimensional and complex optimisation problems. Finally, the proposed algorithm has been used to solve the single machine scheduling problem and the results show that the proposed SAC and HCA-BA outperformed the basic BA in almost all the considered instances, in particular when the complexity of the problem increases.

AB - This paper focuses on improvements to the Bees Algorithm (BA) with slope angle computation and Hill Climbing Algorithm (SACHCA) during the local search process. First, the SAC was employed to determine the inclination of the current sites. Second, according to the slope angle, the HCA was utilised to guide the algorithm to converge to the local optima. This enabled the global optimum of the given problem to be found faster and more precisely by focusing on finding the available local optima first before turning the attention on the global optimum. The proposed enhancements to the BA have been tested on continuous-type benchmark functions and compared with other optimisation techniques. The results show that the proposed algorithm performed better than other algorithms on most of the benchmark functions. The enhanced BA performs better than the basic BA, in particular on higher dimensional and complex optimisation problems. Finally, the proposed algorithm has been used to solve the single machine scheduling problem and the results show that the proposed SAC and HCA-BA outperformed the basic BA in almost all the considered instances, in particular when the complexity of the problem increases.

U2 - 10.1080/21693277.2014.976321

DO - 10.1080/21693277.2014.976321

M3 - Article

VL - 3

SP - 3

EP - 19

JO - Production and Manufacturing Research

JF - Production and Manufacturing Research

SN - 2169-3277

IS - 1

ER -