Improved Artificial Bee Colony for Design of a Reconfigurable Antenna Array With Discrete Phase Shifters

Li, Xiangtao; Zhao, Xiaowei; Wang, J. N.; Yin, Minghao

doi:10.2528/pierc11100803

Cited by 13 publications

(11 citation statements)

References 17 publications

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“…Inspired by this algorithm, the control parameter, i.e., modification rate (MR) is used. In order to produce a candidate food position v ij from the current memorized x ij , improved ABC algorithm uses the following expression [30]:…”

Section: Modified Artificial Bee Colony (Mabc) Algorithmmentioning

confidence: 99%

“…Despite the simplicity and the superiority of ABC algorithm, recent studies reported that it suffers from a poor exploitation process and a slow convergence rate. To overcome these pitfalls, some research papers have introduced modifications to the classical ABC algorithm in order to improve its performance and tackle more complex realworld problems [29,30].…”

Section: Introductionmentioning

confidence: 99%

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A modified ABC algorithm for solving optimal power flow problem

Hardiansyah

2020

Serb J Electr Eng

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This paper presents a modified artificial bee colony (MABC) algorithm for solving the optimal power flow (OPF) problem in power system. Artificial bee colony algorithm is a recent population-based optimization method which has been successfully used in many complex problems. A new mutation strategy inspired from the differential evolution (DE) is introduced in order to improve the exploitation process. The new algorithm is implemented to the OPF problem so as to minimize the total generation cost when considering the equality and inequality constraints. In order to validate of the proposed algorithm, it is applied to the standard IEEE 30-bus test system. The results show that the proposed technique provides better solutions than other heuristic techniques reported in literature.

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Section: Modified Artificial Bee Colony (Mabc) Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A modified ABC algorithm for solving optimal power flow problem

Hardiansyah

2020

Serb J Electr Eng

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“…Inspired by this algorithm, we also use a control parameter, i.e., modification rate (MR). In order to produce a candidate food position v ij from the current memorized x ij , improved ABC algorithm uses the following expression [17]: …”

Section: Modified Artificial Bee Colony (Mabc) Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Modified ABC Algorithm for Solving Non-Convex Dynamic Economic Dispatch Problems

Hardiansyah¹

2016

IJECE

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In this paper, a modified artificial bee colony (MABC) algorithm is presented to solve non-convex dynamic economic dispatch (DED) problems considering valve-point effects, the ramp rate limits and transmission losses. Artificial bee colony algorithm is a recent population-based optimization method which has been successfully used in many complex problems. A new mutation strategy inspired from the differential evolution (DE) is introduced in order to improve the exploitation process. The feasibility of the proposed method is validated on 5 and 10 units test system for a 24 h time interval. The results are compared with the results reported in the literature. It is shown that the optimum results can be obtained more economically and quickly using the proposed method in comparison with the earlier methods. Keyword:Dynamic economic dispatch Modified artificial bee colony algorithm Ramp rate limits Valve-point effects Copyright © 2016 Institute of Advanced Engineering and Science.All rights reserved. Corresponding Author:Hardiansyah, Department of Electrical Engineering, Tanjungpura University, Jalan Ahmad Yani, Pontianak-78124, West Kalimantan, Indonesia. Email: hardi_eka@yahoo.com INTRODUCTIONA power utility needs to ensure that the electrical power is generated with minimum cost. Hence, for economic operation of the system, the total demand must be appropriately shared among the generating units with an objective to minimize the total generation cost of the system. Dynamic economic dispatch (DED) is one of important problems in power system operation and control, which is used to determine the optimal schedule of generating outputs online so as to meet the load demand at the minimum operating cost under various system and operating constraints over the entire dispatch periods. DED is an extension of the conventional economic dispatch (ED) problem that takes into consideration the limits on the ramp rate of generating units to maintain the life of generation equipment [1][2].Since the DED problem was introduced, several optimization techniques and procedures have been used for solving the DED problem with complex objective functions or constraints. There were a number of classical methods that have been applied to solve this problem such as gradient projection method, Lagrange relaxation, and linear programming [3][4][5]. Most of these methods are not applicable for non-smooth or nonconvex cost functions. To overcome this problem, many stochastic optimization methods have been employed to solve the DED problem, such as genetic algorithm (GA) [6], simulated annealing (SA) [7], differential evolution (DE) [8], particle swarm optimization (PSO) [9], hybrid EP and SQP [10], deterministically guided PSO [11], artificial bee colony (ABC) algorithm [12], and imperialist competitive algorithm (ICA) [13]. Many of these techniques have proven their effectiveness in solving the DED problem without any or fewer restrictions on the shape of the cost function curves.Swarm intelligence has become a research interest to different ...

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“…Several types of ABC's generation are Parallel ABC, Smart Flight ABC, Multiple Onlooker ABC, Modified ABC and Improved ABC. According to these developments are known that main advantages are better abilities to get out of optimal results and superior performances for finding solutions [10], [17], [18], [19], [20], [21], [2]. From these works are devoted to the future studies in convergence speeds, searching mechanisms and real applications.…”

Section: Introductionmentioning

confidence: 99%

Solving Combined Economic and Emission Dispatch Using Harvest Season Artificial Bee Colony Algorithm Considering Food Source Placements and Modified Rates

Afandi

Miyauchi²

2014

ijeei

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This paper presents performances of a harvest season artificial bee colony (HSABC) algorithm for obtaining the best solution of a combined economic and emission dispatch (CEED). Two strategies of placement are applied to IEEE-30 bus system for solving the CEED problem under some constraints. Modified rates and various distances are also used to demonstrate HSABC's performances. Simulation results show that two placement strategies have different implications for the CEED, application of various modified rates and distances affect to convergence speeds, minimum results are searched in different starting points at the first iteration and the total number of food sources gives effects to the HSABC's performances.

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Improved Artificial Bee Colony for Design of a Reconfigurable Antenna Array With Discrete Phase Shifters

Cited by 13 publications

References 17 publications

A modified ABC algorithm for solving optimal power flow problem

A modified ABC algorithm for solving optimal power flow problem

A Modified ABC Algorithm for Solving Non-Convex Dynamic Economic Dispatch Problems

Solving Combined Economic and Emission Dispatch Using Harvest Season Artificial Bee Colony Algorithm Considering Food Source Placements and Modified Rates

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