Bees Algorithm for multimodal function optimisation

Zhou, ZD; Xie, YQ; Pham, Duc Truong; Kamsani, Silah Hayati

doi:10.1177/0954406215576063

Cited by 11 publications

(5 citation statements)

References 37 publications

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“…Since its first introduction in 2005 by Professor Pham et al, this algorithm has been widely proposed by many researchers as a powerful optimisation tool to solve several problems in different fields. This is due to the wide spectrum of advantages such as simplicity and efficaciousness [33][34][35][36][37].…”

Section: The Proposed Optimisation Technique and Objective Functionmentioning

confidence: 99%

The Bees Algorithm Tuned Sliding Mode Control for Load Frequency Control in Two-Area Power System

2021

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This paper proposes a design of Sliding Mode Control (SMC) for Load Frequency Control (LFC) in a two-area electrical power system. The mathematical model design of the SMC is derived based on the parameters of the investigated system. In order to achieve the optimal use of the proposed controller, an optimisation tool called the Bees Algorithm (BA) is suggested in this work to tune the parameters of the SMC. The dynamic performance of the power system with SMC employed for LFC is studied by applying a load disturbance of 0.2 pu in area one. To validate the supremacy of the proposed controller, the results are compared with those of recently published works based on Fuzzy Logic Control (FLC) tuned by Teaching–Learning-Based Optimisation (TLBO) algorithm and the traditional PID optimised by Lozi map-based Chaotic Optimisation Algorithm (LCOA). Furthermore, the robustness of SMC-based BA is examined against parametric uncertainties of the electrical power system by simultaneous changes in certain parameters of the testbed system with 40% of their nominal values. Simulation results prove the superiority and the robustness of the proposed SMC as an LFC system for the investigated power system.

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Section: The Proposed Optimisation Technique and Objective Functionmentioning

confidence: 99%

The Bees Algorithm Tuned Sliding Mode Control for Load Frequency Control in Two-Area Power System

2021

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“…In these sections, many searches are made in the neighborhood of optimum solutions, similar to doing guidance with real bees dance. In addition, random searches continue in the global search section, thus avoiding local optimum values [25]. The problem in this study is in combinatorial structure.…”

Section: The Online Bees Algorithmmentioning

confidence: 99%

Using Online Bees Algorithm for Real-time Permutation Flow Shop Problem in Car Disassembly Line

Şahin¹,

Wang²

2021

Preprint

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The automobile disassembly line is a typical permutation flow shop problem (PFSP). In the automobile disassembly line, the goal of the research is to minimize the completion time of scheduling with optimizing the disassembly order of vehicles. However, disassembly time was uncertain at the initial stage as the consuming time of cars’ specific sequence only could be roughly estimated, which make the PFSP in automobile disassembly line unlike the traditional ones. In this study, the real-time PFSP problem in automobile disassembly line was defined and well solved with the proposed online Bees Algorithm (O-BA). The algorithm has been prepared in Matlab/Simulink to work in real-time. Time consumed by each component of each vehicle was roughly estimated based on engineer’s experience. First optimisation was carried out to decide the disassembly order of vehicles to be disassembled. When each component was disassembled, the real consuming time value was updated with the detecting system which was realized in Simulink. Then the O-BA was activated and created the new solution for the disassembly order of vehicles which were still not entering the disassembly line. The proposed O-BA algorithm has an online structure and conducted the optimisation with distinguishing whether the vehicles to be disassembled were entering the disassembly line. The result shows the O-BA with the detecting system was succeeded in realizing real-time PFSP in the disassembly line. Moreover, the method proposed in this study was suitable for solving the same kind of real-time PFSP in the assembly line or disassembly line.

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“…The pseudo code for the algorithm is shown in its simplest form in Figure 6. As detailed in leading studies, [33][34][35][36][37][38][39][40][41] the algorithm requires a number of parameters to be set, namely: number of scout bees (n), number of sites selected for exploitation out of n visited sites (m), number of top-rated (elite) sites among the m selected sites (e), number of bees recruited for the best e sites (nep), number of recruited for the other (m-e) selected sites (nsp), initial size of each patch (a patch is a region in search space that includes a visited site and its neighbourhood) and stopping criterion is iteration number (itr). The algorithm begins with the n scout bees being placed haphazardly in the search space.…”

Section: The Bees Algorithm and Genetic Algorithm For Pid Controller mentioning

confidence: 99%

Optimisation of a PID controller for a two-floor structure under earthquake excitation based on the bees algorithm

Şen

Tınkır

Kalyoncu

2018

Journal of Low Frequency Noise, Vibration and Active Control

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The control of vibration and displacement in structures under seismic excitation is very challenging, and designing a structural control system against disturbances has drawn great attention. This paper concentrates on implementing the bees algorithm to tune gains of traditional PID controller for active vibration control of a building-like structure with two floors under Northridge Earthquake excitation. Bees algorithm is a diverse method to ensure an efficient solution for optimisation of a controller according to customary trial-error design methods. The main aim of this study is optimisation of K P , K I and K D gains with bees algorithm in order to obtain a more effective PID controller to suppress vibrations of the floors during the earthquake excitation. After definition of the system and bees algorithm, PID controller offline tuned with bees algorithm using mathematical model of system. Moreover, the aim is to compare the performances of the BA with an existing optimisation method, genetic algorithm (GA), implemented on the system. The paper presents the experimental results that were obtained from the structure system to show the efficiency of the tuned PID controller. As a result, the performance and effectiveness of the tuned PID controller are investigated and verified experimentally. The displacements and accelerations of the floors and the cart are decreased considerably. The experimental responses of the system are given in graphical form.

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Bees Algorithm for multimodal function optimisation

Cited by 11 publications

References 37 publications

The Bees Algorithm Tuned Sliding Mode Control for Load Frequency Control in Two-Area Power System

The Bees Algorithm Tuned Sliding Mode Control for Load Frequency Control in Two-Area Power System

Using Online Bees Algorithm for Real-time Permutation Flow Shop Problem in Car Disassembly Line

Optimisation of a PID controller for a two-floor structure under earthquake excitation based on the bees algorithm

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