scholarly journals A New Hybrid BA_ABC Algorithm for Global Optimization Problems

Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1749 ◽  
Author(s):  
Gülnur Yildizdan ◽  
Ömer Kaan Baykan
Keyword(s):  
Global Optimization ◽  
Large Scale ◽  
Optimization Problems ◽  
Statistical Tests ◽  
Global Search ◽  
Small Scale ◽  
Test Functions ◽  
Engineering Design Problems ◽  
Scale Test ◽  
Search Capability

Bat Algorithm (BA) and Artificial Bee Colony Algorithm (ABC) are frequently used in solving global optimization problems. Many new algorithms in the literature are obtained by modifying these algorithms for both constrained and unconstrained optimization problems or using them in a hybrid manner with different algorithms. Although successful algorithms have been proposed, BA’s performance declines in complex and large-scale problems are still an ongoing problem. The inadequate global search capability of the BA resulting from its algorithm structure is the major cause of this problem. In this study, firstly, inertia weight was added to the speed formula to improve the search capability of the BA. Then, a new algorithm that operates in a hybrid manner with the ABC algorithm, whose diversity and global search capability is stronger than the BA, was proposed. The performance of the proposed algorithm (BA_ABC) was examined in four different test groups, including classic benchmark functions, CEC2005 small-scale test functions, CEC2010 large-scale test functions, and classical engineering design problems. The BA_ABC results were compared with different algorithms in the literature and current versions of the BA for each test group. The results were interpreted with the help of statistical tests. Furthermore, the contribution of BA and ABC algorithms, which constitute the hybrid algorithm, to the solutions is examined. The proposed algorithm has been found to produce successful and acceptable results.

scholarly journals Hybridization of Adaptive Differential Evolution with an Expensive Local Search Method

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Rashida Adeeb Khanum ◽  
Muhammad Asif Jan ◽  
Nasser Mansoor Tairan ◽  
Wali Khan Mashwani
Keyword(s):  
Global Optimization ◽  
Local Search ◽  
Differential Evolution ◽  
Large Scale ◽  
Optimization Problems ◽  
Neighborhood Search ◽  
Test Problems ◽  
Adaptive Differential Evolution ◽  
External Archive ◽  
Search Capability

Differential evolution (DE) is an effective and efficient heuristic for global optimization problems. However, it faces difficulty in exploiting the local region around the approximate solution. To handle this issue, local search (LS) techniques could be hybridized with DE to improve its local search capability. In this work, we hybridize an updated version of DE, adaptive differential evolution with optional external archive (JADE) with an expensive LS method, Broydon-Fletcher-Goldfarb-Shano (BFGS) for solving continuous unconstrained global optimization problems. The new hybrid algorithm is denoted by DEELS. To validate the performance of DEELS, we carried out extensive experiments on well known test problems suits, CEC2005 and CEC2010. The experimental results, in terms of function error values, success rate, and some other statistics, are compared with some of the state-of-the-art algorithms, self-adaptive control parameters in differential evolution (jDE), sequential DE enhanced by neighborhood search for large-scale global optimization (SDENS), and differential ant-stigmergy algorithm (DASA). These comparisons reveal that DEELS outperforms jDE and SDENS except DASA on the majority of test instances.

scholarly journals A Novel Bat Algorithm with Multiple Strategies Coupling for Numerical Optimization

Mathematics ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 135 ◽  
Author(s):  
Yechuang Wang ◽  
Penghong Wang ◽  
Jiangjiang Zhang ◽  
Zhihua Cui ◽  
Xingjuan Cai ◽  
...  
Keyword(s):  
Global Optimization ◽  
Heuristic Algorithm ◽  
Numerical Optimization ◽  
Optimization Problems ◽  
Bat Algorithm ◽  
Global Search ◽  
Excellent Performance ◽  
Multiple Strategies ◽  
Search Capability

A bat algorithm (BA) is a heuristic algorithm that operates by imitating the echolocation behavior of bats to perform global optimization. The BA is widely used in various optimization problems because of its excellent performance. In the bat algorithm, the global search capability is determined by the parameter loudness and frequency. However, experiments show that each operator in the algorithm can only improve the performance of the algorithm at a certain time. In this paper, a novel bat algorithm with multiple strategies coupling (mixBA) is proposed to solve this problem. To prove the effectiveness of the algorithm, we compared it with CEC2013 benchmarks test suits. Furthermore, the Wilcoxon and Friedman tests were conducted to distinguish the differences between it and other algorithms. The results prove that the proposed algorithm is significantly superior to others on the majority of benchmark functions.

scholarly journals A Hybrid Whale Optimization Algorithm for Global Optimization

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1477
Author(s):  
Chun-Yao Lee ◽  
Guang-Lin Zhuo
Keyword(s):  
Global Optimization ◽  
Optimization Algorithm ◽  
Optimization Problems ◽  
Whale Optimization Algorithm ◽  
Initial Population ◽  
Test Functions ◽  
Benchmark Test ◽  
Thermal Exchange ◽  
Whale Optimization ◽  
Benchmark Test Functions

This paper proposes a hybrid whale optimization algorithm (WOA) that is derived from the genetic and thermal exchange optimization-based whale optimization algorithm (GWOA-TEO) to enhance global optimization capability. First, the high-quality initial population is generated to improve the performance of GWOA-TEO. Then, thermal exchange optimization (TEO) is applied to improve exploitation performance. Next, a memory is considered that can store historical best-so-far solutions, achieving higher performance without adding additional computational costs. Finally, a crossover operator based on the memory and a position update mechanism of the leading solution based on the memory are proposed to improve the exploration performance. The GWOA-TEO algorithm is then compared with five state-of-the-art optimization algorithms on CEC 2017 benchmark test functions and 8 UCI repository datasets. The statistical results of the CEC 2017 benchmark test functions show that the GWOA-TEO algorithm has good accuracy for global optimization. The classification results of 8 UCI repository datasets also show that the GWOA-TEO algorithm has competitive results with regard to comparison algorithms in recognition rate. Thus, the proposed algorithm is proven to execute excellent performance in solving optimization problems.

scholarly journals Investigation of Improved Cooperative Coevolution for Large-Scale Global Optimization Problems

Algorithms ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 146
Author(s):  
Aleksei Vakhnin ◽  
Evgenii Sopov
Keyword(s):  
Global Optimization ◽  
Evolutionary Algorithms ◽  
Numerical Experiments ◽  
Large Scale ◽  
Optimization Problems ◽  
State Of The Art ◽  
Fixed Number ◽  
High Dimensional ◽  
Cooperative Coevolution ◽  
Large Scale Problems

Modern real-valued optimization problems are complex and high-dimensional, and they are known as “large-scale global optimization (LSGO)” problems. Classic evolutionary algorithms (EAs) perform poorly on this class of problems because of the curse of dimensionality. Cooperative Coevolution (CC) is a high-performed framework for performing the decomposition of large-scale problems into smaller and easier subproblems by grouping objective variables. The efficiency of CC strongly depends on the size of groups and the grouping approach. In this study, an improved CC (iCC) approach for solving LSGO problems has been proposed and investigated. iCC changes the number of variables in subcomponents dynamically during the optimization process. The SHADE algorithm is used as a subcomponent optimizer. We have investigated the performance of iCC-SHADE and CC-SHADE on fifteen problems from the LSGO CEC’13 benchmark set provided by the IEEE Congress of Evolutionary Computation. The results of numerical experiments have shown that iCC-SHADE outperforms, on average, CC-SHADE with a fixed number of subcomponents. Also, we have compared iCC-SHADE with some state-of-the-art LSGO metaheuristics. The experimental results have shown that the proposed algorithm is competitive with other efficient metaheuristics.

scholarly journals An improved arithmetic optimization algorithm with forced switching mechanism for global optimization problems

2022 ◽  
Vol 19 (1) ◽  
pp. 473-512
Author(s):  
Rong Zheng ◽  
◽  
Heming Jia ◽  
Laith Abualigah ◽  
Qingxin Liu ◽  
...  
Keyword(s):  
Optimization Algorithm ◽  
Optimization Problems ◽  
Heuristic Method ◽  
Population Diversity ◽  
Test Functions ◽  
Design Problems ◽  
Local Optima ◽  
Switching Mechanism ◽  
Engineering Design Problems

<abstract> <p>Arithmetic optimization algorithm (AOA) is a newly proposed meta-heuristic method which is inspired by the arithmetic operators in mathematics. However, the AOA has the weaknesses of insufficient exploration capability and is likely to fall into local optima. To improve the searching quality of original AOA, this paper presents an improved AOA (IAOA) integrated with proposed forced switching mechanism (FSM). The enhanced algorithm uses the random math optimizer probability (<italic>RMOP</italic>) to increase the population diversity for better global search. And then the forced switching mechanism is introduced into the AOA to help the search agents jump out of the local optima. When the search agents cannot find better positions within a certain number of iterations, the proposed FSM will make them conduct the exploratory behavior. Thus the cases of being trapped into local optima can be avoided effectively. The proposed IAOA is extensively tested by twenty-three classical benchmark functions and ten CEC2020 test functions and compared with the AOA and other well-known optimization algorithms. The experimental results show that the proposed algorithm is superior to other comparative algorithms on most of the test functions. Furthermore, the test results of two training problems of multi-layer perceptron (MLP) and three classical engineering design problems also indicate that the proposed IAOA is highly effective when dealing with real-world problems.</p> </abstract>

scholarly journals Modifikasi alat cakram untuk proses pembelajaran

2021 ◽  
Vol 2 (2) ◽  
pp. 180-188
Author(s):  
Laras Gita Kinanti ◽  
Utvi Hinda Zhannisa ◽  
Tubagus Herlambang
Keyword(s):  
Physical Education ◽  
Large Scale ◽  
Field Trials ◽  
Small Scale ◽  
Plate Waste ◽  
Education Material ◽  
Teachers And Students ◽  
Student Questionnaire ◽  
Scale Test ◽  
Expert Validation

The purpose of this research is to modify a simple disc device for learning physical education. The research method used was the development of Borg & Gall, namely (1) collecting information, (2) developing the initial form (in the form of a disc tool model), (3) expert validation testing, namely using 1 validation of athletic experts and one physical education learning expert, and small-scale trials using questionnaires and analysis, (4) revision of the first product design, based on the results of experts and small-scale trials (20 students), (5) field trials (48 students), (6) final product revision, (7) the final result of the modification produced through revision of field trials.The results of expert validation were carried out by 2 validities, namely validation in the field of athletic experts and validation of physical education material experts, and the results obtained in each validity were the first for the validation results in the field of athletic experts getting a percentage of 87.6% calcification (Good) , the second for the validation results in the field of Physical Education material experts got a percentage of 83.0% with the classification (Good). The results of the student questionnaire on a small scale test got a percentage of 86.6% (good). the results of the questionnaire on large-scale test students got a percentage of 81.8% (good).The conclusion and advice is that the development of a modified model of disc throwing tools with iron plate waste media can be used as an alternative to discus throwing. With the modification of disc throwing, teachers and students can be helped in learning discusses, students are interested and more active and excited in learning throw the disc.

scholarly journals Pengembangan model bermain sepakbola untuk meningkatkan aspek psikologis anak usia 12 -13 tahun di Yogyakarta

2016 ◽  
Vol 4 (1) ◽  
pp. 34
Author(s):  
Muna Aprilianto ◽  
Tomoliyus Tomoliyus
Keyword(s):  
Large Scale ◽  
Field Studies ◽  
Development Stage ◽  
Psychological Aspects ◽  
Average Score ◽  
Small Scale ◽  
Scale Test ◽  
Preliminary Research ◽  
Two Stages ◽  
Research Stage

Penelitian ini bertujuan untuk menghasilkan buku pedoman bermain sepakbola untuk meningkatkan aspek psikologis (semangat, gembira, dan disiplin) anak usia 12-13 tahun di Yogyakarta. Penelitian ini merupakan penelitian dan pengembangan yang terdiri atas dua tahapan yaitu tahap penelitian pendahuluan terdiri dari kajian literatur, kajian penelitian relevan, studi lapangan dan tahap pengembangan terdiri perencanaan, validasi ahli, uji skala kecil, dan uji skala besar. Peneliti ini mengambil sampel dari sekolah sepakbola di Yogyakarta. Teknik sampling yang digunakan adalah purposive sampling. Pada uji coba skala kecil dilakukan di SSB Real Madrid melibatkan 10 siswa dan satu orang pelatih. Pada uji coba skala besar dilakukan di dua tempat yaitu di SSB Real Madrid dan SSB Bina Putra Jaya Sleman melibatkan 38 siswa dan dua pelatih. Analsis data dalam penelitian ini menggunakan teknik analisis deskriptif kuantitatif dan kualitatif. Hasil validasi menunjukkan model bermain sepakbola anak usia 12-13 tahun layak untuk diuji cobakan. Berdasarkan Hasil pelaksanaan pada uji coba skala kecil dan besar secara substansi isi dan pelaksanaan tergolong sangat baik. Hasil penilaian efektivitas model tehadap psikologis anak berupa semangat, gembira, dan disiplin mengalami peningkatan: nilai pertemuan kedua lebih tinggi dari pertemuan pertama. Dapat disimpulkan model bermain sepakbola anak usia 12-13 tahun efektif untuk meningkatkan aspek psikologis berupa semangat, gembira, dan disiplin siswa dalam melakukan latihan sepakbola.Kata Kunci: model, bermain, psikologis, sekolah sepakbola Development a playing soccer model to improve the psychological aspects of 12-13 years old children in Yogyakarta AbstractThis research aims to develop a playing soccer model to improve the psychological aspects (spirit, joy, and discipline) of 12-13 years old children in Yogyakarta. This study is a research and development which consists of two stages. The Preliminary research stage and development stage. The Preliminary research stage consisted of a literature review, relevant research studies and field studies. The Development stage consisted of planning, validation expert, small-scale test, and test large scale. The Validation involve three people experts. The sampel of take it from soccer school in Yogyakarta. The small-scale tryout was conducted on 10 students and one coach of Real Madrid Soccer School in Yogyakarta. The large-scale trials were conducted with two soccer school on 38 students and two coach of Yogyakarta Real Madrid Soccer School and Sleman Bina Putra Jaya Soccer School. The resul is a playing soccer model for children aged 12-13 years with the title "Playing Soccer in Practice to Improve Psychological Aspects". Based on the small-scale tryout and the small-scale tryout content implementation aspects are in an excellent category. The Psychological development of students assessment resulting in the form of passion, joy, and discipline in playing soccer show improvement: score of the second meeting is greater than the average score of the first meeting, thus it can be concluded thaat the playing soccer model for children age 12-13 years is effective to improve students’ psychological aspects, including the aspects of spirit, joy, and discipline in doing soccer practice.Keywords: models, play, psychological, soccer school

Four Points Bending Tests on Large Scale Welded Pipes Containing a Through-Wall Defect: Fatigue and Fracture Analysis

2014 ◽  
Author(s):  
M. Bourgeois ◽  
T. Le Grasse ◽  
Y. Kayser
Keyword(s):  
Large Scale ◽  
Structural Integrity ◽  
Atomic Energy Commission ◽  
Electrical Potential ◽  
Potential Drop ◽  
Small Scale ◽  
Butt Weld ◽  
Bending Tests ◽  
Scale Test ◽  
Fracture Tests

Within the framework of European project STYLE (Structural integrity for lifetime management), fracture tests on two large scale pipes containing a through wall crack have been performed. Two Mock-ups have been tested: MU1 is a narrow gap Inconel Dissimilar Metals, provided and designed by AREVA France, and MU2 is a an austenitic steel butt-weld with a thermally aged weld repair austenitic weld, provided by EDF British Energy. The four-points bending tests were carried out by the French Alternative Energies and Atomic Energy Commission (CEA), in order to study the mechanical properties and integrity of component such as welding pipes. A through wall crack was machined in the both pipes. After a fatigue pre-cracking step carried out at RT, the monotonic fracture test was performed (at 300°C on MU1). Optical camera and Electrical Potential Drop Method have allowed following the crack growth during fatigue and final fracture stages. The observations made post-mortem showed ductile tearing of a few millimeters in those pipes. The first part of this paper is devoted to the four-points bending tests. The second part of this paper deals with first numerical analysis related to the Mock-up-1. Previous results concerning the mechanical characterizations of the constitutive materials are discussed. Fracture mechanics small scale specimens are interpreted using FE Analysis to obtain the fracture parameters used in global approaches. First computation is shown on the Mock-up-1 in order to predict the behavior of the large scale test mechanical and fracture behavior.

scholarly journals Differential Evolution with Novel Mutation and Adaptive Crossover Strategies for Solving Large Scale Global Optimization Problems

2017 ◽  
Vol 2017 ◽  
pp. 1-18 ◽  
Author(s):  
Ali Wagdy Mohamed ◽  
Abdulaziz S. Almazyad
Keyword(s):  
Global Optimization ◽  
Differential Evolution ◽  
Large Scale ◽  
Optimization Problems ◽  
Differential Evolution Algorithm ◽  
High Dimensional ◽  
Gradual Change ◽  
Comparison Results ◽  
Mutation Strategy ◽  
Common Trade

This paper presents Differential Evolution algorithm for solving high-dimensional optimization problems over continuous space. The proposed algorithm, namely, ANDE, introduces a new triangular mutation rule based on the convex combination vector of the triplet defined by the three randomly chosen vectors and the difference vectors between the best, better, and the worst individuals among the three randomly selected vectors. The mutation rule is combined with the basic mutation strategy DE/rand/1/bin, where the new triangular mutation rule is applied with the probability of 2/3 since it has both exploration ability and exploitation tendency. Furthermore, we propose a novel self-adaptive scheme for gradual change of the values of the crossover rate that can excellently benefit from the past experience of the individuals in the search space during evolution process which in turn can considerably balance the common trade-off between the population diversity and convergence speed. The proposed algorithm has been evaluated on the 20 standard high-dimensional benchmark numerical optimization problems for the IEEE CEC-2010 Special Session and Competition on Large Scale Global Optimization. The comparison results between ANDE and its versions and the other seven state-of-the-art evolutionary algorithms that were all tested on this test suite indicate that the proposed algorithm and its two versions are highly competitive algorithms for solving large scale global optimization problems.

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