In a resource-constrained environment project planning and scheduling becomes an extremely complex problem. For real life project schedules multi-mode resource requirements remarkably increase the complexity of and en...
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In a resource-constrained environment project planning and scheduling becomes an extremely complex problem. For real life project schedules multi-mode resource requirements remarkably increase the complexity of and enlarge the respective solution spaces. Therefore schedulers require systematic methodologies compatible with the real world implementations in order to generate cost effective schedules. Similarly, plastic injection molding is known to be a "make-to order" process. The manufacturing of the mold which is a unique and essential component of plastic injection is considered kind of a project. The aim of this study is set to investigate the possibility of utilizing bees algorithm for single-resource, multi-mode, resource-constrained mold project scheduling in order to generate a systematic approach to solve the problems of this nature. A Bee-Based Mold Scheduling Model is therefore proposed and employed on a set of problems with different dimensions for the proof of concept. Detail description of an injection molding project together with respective performance analysis is also provided. After the implementation of the proposed methodology, it is well proven that, even for high number of activities and limited resources, the proposed method generates suitable schedules for the projects of this kind the implementation and respective modelling is explained and the results are discussed in detail within the text. (C) 2017 Elsevier Ltd. All rights reserved.
作者：
Guney, K.Onay, M.Erciyes Univ
Fac Engn Dept Elect & Elect Engn TR-38039 Kayseri Turkey Erciyes Univ
Civil Aviat Sch Dept Aircraft Elect & Elect TR-38039 Kayseri Turkey
In this paper, bees algorithm (BA) has been used for null steering in the antenna radiation pattern by controlling the phase-only and the complex weights (both the amplitude and phase) of the array elements. The BA is...
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In this paper, bees algorithm (BA) has been used for null steering in the antenna radiation pattern by controlling the phase-only and the complex weights (both the amplitude and phase) of the array elements. The BA is an optimization algorithm inspired by the behavior of the honey bees to find the optimal way of harvesting food resources around the hive. Simulation results for Chebyshev patterns with the imposed single, multiple and broad nulls are given to show the effectiveness of the proposed method. The sensitivity of the nulling patterns due to small variations of the element phases is also investigated. (C) 2009 Elsevier Ltd. All rights reserved.
作者：
Guney, K.Onay, M.Erciyes Univ
Fac Engn Dept Elect & Elect Engn TR-38039 Kayseri Turkey Erciyes Univ
Civil Aviat Sch Dept Aircraft Elect & Elect TR-38039 Kayseri Turkey
This article describes a method of designing a reconfigurable dual-beam linear antenna array using bees algorithm (BA). The BA is an optimization algorithm inspired by the behavior of the honey bees to find the optima...
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This article describes a method of designing a reconfigurable dual-beam linear antenna array using bees algorithm (BA). The BA is an optimization algorithm inspired by the behavior of the honey bees to find the optimal way of harvesting food resources around the hive. The proposed method is very simple and can be used directly in practice to synthesize multiple beam antenna arrays with digital attenuators and digital phase shifters. A good agreement between the desired pattern and the synthesized pattern using BA is obtained. (C) 2008 Wiley Periodicals, Inc.
The purpose of this research is to automatically construct multiple equivalent test forms that have equivalent qualities indicated by test information functions based on item response theory. There has been a trade-of...
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The purpose of this research is to automatically construct multiple equivalent test forms that have equivalent qualities indicated by test information functions based on item response theory. There has been a trade-off in previous studies between the computational costs and the equivalent qualities of test forms. To alleviate this problem, we propose an automated system of test construction based on the bees algorithm in parallel computing. We demonstrate the effectiveness of the proposed system through various experiments.
bees algorithm (BA) is a new member of meta-heuristics. BA tries to model natural behavior of honey bees in food foraging. Honey bees use several mechanisms like waggle dance to optimally locate food sources and to se...
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bees algorithm (BA) is a new member of meta-heuristics. BA tries to model natural behavior of honey bees in food foraging. Honey bees use several mechanisms like waggle dance to optimally locate food sources and to search new ones. This makes them a good candidate for developing new algorithms for solving optimization problems. In this paper a brief review of BA is first given, afterwards development of a BA for solving generalized assignment problems (GAP) with an ejection chain neighborhood mechanism is presented. GAP is a NP-hard problem. Many meta-heuristic algorithms were proposed for its solution. So far BA is generally applied to continuous optimization. In order to investigate the performance of BA on a complex integer optimization problem, an attempt is made in this paper. An extensive computational study is carried out and the results are compared with several algorithms from the literature. (C) 2009 Elsevier Inc. All rights reserved.
The aim of multimodal optimisation is to find significant optima of a multimodal objective function including its global optimum. Many real-world applications are multimodal optimisation problems requiring multiple op...
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The aim of multimodal optimisation is to find significant optima of a multimodal objective function including its global optimum. Many real-world applications are multimodal optimisation problems requiring multiple optimal solutions. The bees algorithm is a global optimisation procedure inspired by the foraging behaviour of honeybees. In this paper, several procedures are introduced to enhance the algorithm's capability to find multiple optima in multimodal optimisation problems. In the proposed bees algorithm for multimodal optimisation, dynamic colony size is permitted to automatically adapt the search effort to different objective functions. A local search approach called balanced search technique is also proposed to speed up the algorithm. In addition, two procedures of radius estimation and optima elitism are added, to respectively enhance the bees algorithm's ability to locate unevenly distributed optima, and eliminate insignificant local optima. The performance of the modified bees algorithm is evaluated on well-known benchmark problems, and the results are compared with those obtained by several other state-of-the-art algorithms. The results indicate that the proposed algorithm inherits excellent properties from the standard bees algorithm, obtaining notable efficiency for solving multimodal optimisation problems due to the introduced modifications.
bees algorithm is one of the swarm intelligence based heuristics which tries to model natural behaviour of honey bees in food foraging and used to solve optimization problems. On the other hand, Two-sided Assembly Lin...
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bees algorithm is one of the swarm intelligence based heuristics which tries to model natural behaviour of honey bees in food foraging and used to solve optimization problems. On the other hand, Two-sided Assembly Line Balancing Problem is a generalization of simple Assembly Line Balancing Problem where different assembly tasks are carried out on the same product in parallel at both left and right sides of the line. Two-sided assembly lines are generally employed for the assembly of large-sized products such as buses and trucks. Furthermore, many real life problems contain imprecise objectives and Fuzzy Multi-objective Programming gives an opportunity to handle such situations. In this study, Two-sided Assembly Line Balancing Problem is considered more realistically by employing positional, zoning and synchronous task constraints and by utilizing fuzzy approaches so as to maximize work slackness index and line efficiency, and minimize total balance delay. For solving this problem bees algorithm is used as a search mechanism for obtaining good solutions and extensive computational results are presented.
Intrusion detection systems (IDSs) have become a necessary component of computers and information security framework. IDSs commonly deal with a large amount of data traffic and these data may contain redundant and uni...
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Intrusion detection systems (IDSs) have become a necessary component of computers and information security framework. IDSs commonly deal with a large amount of data traffic and these data may contain redundant and unimportant features. Choosing the best quality of features that represent all of the data and exclude the redundant features is a crucial topic in IDSs. In this paper, a new combination approach based on the ID3 algorithm and the bees algorithm (BA) is proposed to select the optimal subset of features for an IDS. The BA is used to generate a subset of features, and the ID3 algorithm is used as a classifier. The proposed model is applied on KDD Cup 99 dataset. The obtained results show that the feature subset generated by the proposed ID3-BA gives a higher accuracy and detection rate with a lower false alarm rate when compared to the results obtained by using all features.
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 o...
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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.
The current paper presents the use of the bees algorithm with Kalman filtering to train a radial basis function (RBF) neural network. An enhanced fuzzy selection system has been developed to choose local search sites ...
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The current paper presents the use of the bees algorithm with Kalman filtering to train a radial basis function (RBF) neural network. An enhanced fuzzy selection system has been developed to choose local search sites depending on the error and training accuracy of the RBF network. The paper provides comparative results obtained when applying RBF neural classifiers trained using the new bees algorithm, the original bees algorithm, and the conventional RBF procedure to an industrial pattern classification problem.
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