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The bees algorithm for workload balancing in examination job assignment

EUROPEAN JOURNAL OF INDUSTRIAL ENGINEERING 2009年第4期3卷 424-435页

作者： Baykasoglu, Adil Ozbakir, Lale Tapkan, Pinar Gaziantep Univ Dept Ind Engn TR-27310 Gaziantep Turkey Erciyes Univ Dept Ind Engn TR-38039 Kayseri Turkey

In this paper, an integer quadratic programming model is proposed for workload balancing in the examination job assignment problem. The proposed model can be classified as part of the 'Generalised Assignment Problem' or GAP, which is known as an NP-hard problem. To solve the proposed model, a relatively new member of the swarm intelligence family known as the bees algorithm (BA) is used. The proposed mathematical model is also solved for nine sets of randomly generated test problems with a very well-known classical optimiser (CPLEX 10.1-MIQP) to present the competitive performance of the BA algorithm. The obtained results show that the proposed BA algorithm is able to generate better solutions with much shorter computational times.

关键词： assignment problems workload balancing metaheuristics swarm optimisation bees algorithm

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Using bees Hill Flux Balance Analysis (BHFBA) for in silico Microbial Strain Optimization

Using Bees Hill Flux Balance Analysis (BHFBA) for <i>in sili...

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5th Asian Conference on Intelligent Information and Database Systems (ACIIDS)

作者： Choon, Yee Wen Bin Mohamad, Mohd Saberi Deris, Safaai Illias, Rosli Md Chai, Lian En Chong, Chuii Khim Univ Teknol Malaysia Fac Comp Sci & Informat Syst Artificial Intelligence & Bioinformat Res Grp Skudai 81310 Johor Malaysia Univ Teknol Malaysia Fac Chem Engn Dept Bioproc Engn Skudai 81310 Johor Malaysia

ISBN: (纸本)9783642365461

Microbial strains can be manipulated to improve product yield and improve growth characteristics. Optimization algorithms are developed to identify the effects of gene knockout on the results. However, this process is often faced the problem of being trapped in local minima and slow convergence due to repetitive iterations of algorithm. In this paper, we proposed bees Hill Flux Balance Analysis (BHFBA) which is a hybrid of bees algorithm, Hill Climbing algorithm and Flux Balance Analysis to solve the problems and improve the performance in predicting optimal sets of gene deletion for maximizing the growth rate and production yield of desired metabolite. Escherichia coli is the model organism in this paper. The list of knockout genes, growth rate and production yield after the deletion are the results from the experiments. BHFBA performed better in term of computational time, stability and production yield.

关键词： bees algorithm Hill Climbing Flux Balance Analysis Microbial Strains Optimization

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A Comparative Study of Improved Artificial Bee Colony algorithms Applied to Multilevel Image Thresholding

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MATHEMATICAL PROBLEMS IN ENGINEERING 2013年第1期2013卷 1-17页

作者： Charansiriphaisan, Kanjana Chiewchanwattana, Sirapat Sunat, Khamron Khon Kaen Univ Fac Sci Dept Comp Sci Khon Kaen 40002 Thailand

Multilevel thresholding is a highly useful tool for the application of image segmentation. Otsu's method, a common exhaustive search for finding optimal thresholds, involves a high computational cost. There has been a lot of recent research into various metaheuristic searches in the area of optimization research. This paper analyses and discusses using a family of artificial bee colony algorithms, namely, the standard ABC, ABC/best/1, ABC/best/2, IABC/best/1, IABC/rand/1, and CABC, and some particle swarm optimization-based algorithms for searching multilevel thresholding. The strategy for an onlooker bee to select an employee bee was modified to serve our purposes. The metric measures, which are used to compare the algorithms, are the maximum number of function calls, successful rate, and successful performance. The ranking was performed by Friedman ranks. The experimental results showed that IABC/best/1 outperformed the other techniques when all of them were applied to multilevel image thresholding. Furthermore, the experiments confirmed that IABC/best/1 is a simple, general, and high performance algorithm.

关键词： bees algorithm SEGMENTATION (Image processing) THRESHOLDING algorithms MATHEMATICAL optimization PARTICLE swarm optimization METAHEURISTIC algorithms

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bees for Block Matching

Bees for Block Matching

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39th Annual Conference of the IEEE Industrial-Electronics-Society (IECON)

作者： Boumazouza, Daoud Sefouane, Yasmine Djeddi, Mohamed Khelouat, Boualem Benatchba, Karima Ecole Natl Super Informat ESI Lab Methodes Concept Syst Algiers Algeria

ISBN: (纸本)9781479902248

Detection of moving objects in a video sequence is a growing field, used in various domains. There are, in the literature, several approaches to detect such movements. In this paper, we will focus on one of these approaches namely block matching. We propose to speed the performances of the block matching algorithm using the bees' algorithm which is known for its efficient exploration of search space as it uses two interesting strategies intensification and diversification. The proposed algorithm, BAforBM, is evaluated and compared to two existing ones: genetic bloc matching algorithm and a block matching algorithm based on PSO (Particule Swarm Optimisation).

关键词： Motion detection Block matching bees algorithm metaheuristic

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Geometrical Optimization of the Overlap in Mixed Adhesive Lap Joints

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JOURNAL OF ADHESION 2013年第12期89卷 948-972页

作者： Bavi, O. Bavi, N. Shishesaz, M. Sharif Univ Technol Inst Nanosci & Nanotechnol Tehran Iran Shahid Chamran Univ Dept Mech Engn Ahvaz Iran

The aim of this research is to optimize the geometry of the overlap in mixed adhesive single- and double-lap joints using a modified version of bees and Genetic algorithms (BA and GA). Accounting for adherends Poisson's ratio in the deduced equilibrium equations, the proposed shear lag model gives a more accurate approximation of joint failure load in comparison with Volkersen's solution. The objective functions used in this work are used separately to maximize the load bearing capacity f and the specific strength (f/w) of the joint. This procedure is applied to optimize aeronautical adhesively bonded assemblies, while taking manufacturing constraints into account. The employed constraints are the application of yield criterion on adherends as well as geometrical constraint on the overlap length. The proposed straightforward procedure provides 18 optimal configurations amid a wide range of changes for optimization variables, among which the designer can take a choice, depending on his/her goal. The efficiency of the two employed algorithms, BA and GA, in searching for the optimum geometrical design of the mixed adhesive joints have also been investigated. The results show the more robust and efficient performance of the modified version of BA over GA in such kinds of engineering problems.

关键词： Aerospace bees algorithm Joint design Lap-Shear Mixed adhesive joints Optimization

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A Simple and Efficient Artificial Bee Colony algorithm

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MATHEMATICAL PROBLEMS IN ENGINEERING 2013年第1期2013卷 1-9页

作者： Xu, Yunfeng Fan, Ping Yuan, Ling Huazhong Univ Sci & Technol Sch Comp Sci & Technol Wuhan 430074 Peoples R China Chinese Peoples Publ Secur Univ Dept Informat Secur Engn Beijing 100038 Peoples R China Hubei Univ Sci & Technol Sch Comp Sci Xianning 437100 Peoples R China

Artificial bee colony (ABC) is a new population-based stochastic algorithm which has shown good search abilities on many optimization problems. However, the original ABC shows slow convergence speed during the search process. In order to enhance the performance of ABC, this paper proposes a new artificial bee colony (NABC) algorithm, which modifies the search pattern of both employed and onlooker bees. A solution pool is constructed by storing some best solutions of the current swarm. New candidate solutions are generated by searching the neighborhood of solutions randomly chosen from the solution pool. Experiments are conducted on a set of twelve benchmark functions. Simulation results show that our approach is significantly better or at least comparable to the original ABC and seven other stochastic algorithms.

关键词： bees algorithm MATHEMATICAL optimization STOCHASTIC analysis STOCHASTIC convergence PERFORMANCE evaluation FUNCTIONS (Mathematics) SIMULATION methods & models POPULATION research

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Crack detection of plate structures using differential quadrature method

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE 2013年第7期227卷 1495-1504页

作者： Moradi, S. Alimouri, P. Shahid Chamran Univ Dept Mech Engn Ahvaz 61355 Iran

In this study, the problem of crack identification in plates is investigated using the differential quadrature method. The crack, which is assumed to be open, is modeled by the extended rotational spring. The crack, with finite length, divides the plate into six segments. Then, the differential quadrature is applied to the governing differential equations of motion of each segment and the corresponding boundary and continuity conditions. An eigenvalue analysis will be performed on the resulting system of algebraic equations to obtain the natural frequencies of the cracked plate. Here, the crack detection practice is considered as an optimization problem, and the location, size, and depth of the crack are regarded as the design variables. The weighted sum of the squared errors between the measured and computed natural frequencies is used as the objective function. The bees algorithm, a swarm-based evolutionary optimization technique, is used to solve the optimization problem. To insure the integrity and robustness of the presented method, extensive experimental case studies are carried out on the cantilever plates having a finite-length open crack parallel to the clamped edge. The results show that the crack parameters can be predicted well by the presented methodology.

关键词： Differential quadrature crack detection cantilever plate bees algorithm

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A hybrid controller based on CPG and ZMP for biped locomotion

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JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY 2013年第11期27卷 3473-3486页

作者： Massah, Amir B. Zamani, Ali Salehinia, Yaser Aliyari, Mahdi Sh Teshnehlab, Mohammad KN Toosi Univ Technol Dept Elect & Comp Engn Tehran Iran KN Toosi Univ Technol Dept Mech Engn Tehran Iran

Biped locomotion has attracted much attention in recent years. The most successful implemented methods in this area are based on two approaches, central pattern generator (CPG) and zero moment point (ZMP). Unfortunately, neither of these concepts can solely solve the movement challenge completely. In this study, we introduce a hybrid controller to combine the advantages of these methods. The proposed controller is based on two major approaches, CPG and ZMP. This hybrid controller is composed of a trajectory control system and a trajectory generator system. The trajectory control system applied to keep the robot stable uses ZMP as a real time control feedback. The trajectory generator system, which is composed of nonlinear oscillators, generates stable motions. The parameters of CPG are tuned by a new two-stage approach using differential evolution (DE) and bees algorithm (BA). Furthermore, performance of the proposed controller is verified using the robotic simulation software Webots.

关键词： bees algorithm Central pattern generator Differential evolution Webots Zero moment point

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Hazmats Transportation Network Design Model with Emergency Response under Complex Fuzzy Environment

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MATHEMATICAL PROBLEMS IN ENGINEERING 2013年第1期2013卷 1-22页

作者： Xu, Jiuping Gang, Jun Lei, Xiao Sichuan Univ State Key Lab Hydraul & Mt River Engn Chengdu 610064 Peoples R China Sichuan Univ Uncertainty Decis Making Lab Chengdu 610064 Peoples R China China Three Gorges Corp Yichang 443002 Peoples R China

A bilevel optimization model for a hazardous materials transportation network design is presented which considers an emergency response teams location problem. On the upper level, the authority designs the transportation network to minimize total transportation risk. On the lower level, the carriers first choose their routes so that the total transportation cost is minimized. Then, the emergency response department locates their emergency service units so as to maximize the total weighted arc length covered. In contrast to prior studies, the uncertainty associated with transportation risk has been explicitly considered in the objective function of our mathematical model. Specifically, our research uses a complex fuzzy variable to model transportation risk. An improved artificial bee colony algorithm with priority-based encoding is also applied to search for the optimal solution to the bilevel model. Finally, the efficiency of the proposed model and algorithm is evaluated using a practical case and various computing attributes.

关键词： HAZARDOUS substances FUZZY mathematics MATHEMATICAL optimization TRANSPORTATION costs ARC length bees algorithm

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On multiple crack detection in beam structures

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JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY 2013年第1期27卷 47-55页

作者： Moradi, Shapour Kargozarfard, Mohammad Hasan Shahid Chamran Univ Dept Mech Engn Ahvaz 61355 Iran

This study presents an inverse procedure to identify multiple cracks in beams using an evolutionary algorithm. By considering the crack detection procedure as an optimization problem, an objective function can be constructed based on the change of the eigenfrequencies and some strain energy parameters. Each crack is modeled by a rotational spring. The changes in natural frequencies due to the presence of the cracks are related to a damage index vector. Then, the bees algorithm, a swarm-based evolutionary optimization technique, is used to optimize the objective function and find the damage index vector, whose positive components show the number and position of the cracks. A second objective function is also optimized to find the crack depths. Several experimental studies on cracked cantilever beams are conducted to ensure the integrity of the proposed method. The results show that the number of cracks as well as their sizes and locations can be predicted well through this method.

关键词： bees algorithm Cantilever beam Modal testing Multiple crack detection

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