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A Bee Colony Optimization Approach for Mixed Blocking Constraints Flow Shop Scheduling Problems

MATHEMATICAL PROBLEMS IN ENGINEERING 2015年第1期2015卷 1-10页

作者： Khorramizadeh, Mostafa Riahi, Vahid Shiraz Univ Technol Dept Math Sci Shiraz 71555313 Iran Shiraz Univ Technol Dept Ind Engn Shiraz 71555313 Iran

The flow shop scheduling problems with mixed blocking constraints with minimization of makespan are investigated. The Taguchi orthogonal arrays and path relinking along with some efficient local search methods are used to develop a metaheuristic algorithm based on bee colony optimization. In order to compare the performance of the proposed algorithm, two well-known test problems are considered. Computational results show that the presented algorithm has comparative performance with well-known algorithms of the literature, especially for the large sized problems.

关键词： bees algorithm MATHEMATICAL optimization FLOW shop scheduling PROBLEM solving TAGUCHI methods (Quality control) ORTHOGONAL arrays

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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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A Swarm Intelligent algorithm Based Route Maintaining Protocol for Mobile Sink Wireless Sensor Networks

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MATHEMATICAL PROBLEMS IN ENGINEERING 2015年第1期2015卷 1-10页

作者： Wu, Xiaoming Wang, Yinglong Hu, Yifan Shandong Univ Sci & Technol Coll Informat Sci & Engn Qingdao 266590 Peoples R China Natl Supercomp Ctr Jinan Shandong Comp Sci Ctr Jinan 250014 Peoples R China Shandong Prov Key Lab Comp Network Jinan 250014 Peoples R China

Recent studies have shown that mobile sink can be a solution to solve the problem that energy consumption of sensor nodes is not balanced in wireless sensor networks (WSNs). Caused by the sink mobility, the paths between the sensor nodes and the sink change frequently and have profound influence on the lifetime of WSN. It is necessary to design a protocol that can find efficient routings between the mobile sink and nodes but does not consume too many network resources. In this paper, we propose a swarm intelligent algorithm based route maintaining protocol to resolve this issue. The protocol utilizes the concentric ring mechanism to guide the route researching direction and adopts the optimal routing selection to maintain the data delivery route in mobile sink WSN. Using the immune based artificial bee colony (IABC) algorithm to optimize the forwarding path, the routing maintaining protocol could find an alternative routing path quickly and efficiently when the coordinate of sink is changed in WSN. The results of our extensive experiments demonstrate that our proposed route maintaining protocol is able to balance the network traffic load and prolong the network lifetime.

关键词： SWARM intelligence WIRELESS sensor networks ENERGY consumption WIRELESS sensor nodes bees algorithm DATA Traffic Management System (Computer system)

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Bee algorithms for parallel two-sided assembly line balancing problem with walking times

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APPLIED SOFT COMPUTING 2016年 39卷 275-291页

作者： Tapkan, Pinar Ozbakir, Lale Baykasoglu, Adil Erciyes Univ Dept Ind Engn Kayseri Turkey Dokuz Eylul Univ Dept Ind Engn Izmir Turkey

Production lines, designed in a serial manner, have attracted the attention of researchers for many years. Line efficiency, throughput time and workload balancing are the main concerns regarding assembly lines, due to the high volume production. Recently, specific assembly line configurations, such as two-sided and parallel lines, have been addressed by researchers within the operational levels of production. Parallel two-sided assembly lines, rather a new research area, allocate more flexible workers and reduce throughput time by incorporating the advantages of two-sided and parallel assembly lines. Since parallel two-sided assembly lines are utilized to produce large-scale products, such as automobiles, trucks, and buses in industry;they also require a significant worker movement between parallel lines because of the unavoidable walking distances between lines. In this respect, different from the existing literature, walking distances have been included in parallel two-sided assembly line balancing problem. The main purpose of this paper is to introduce parallel two-sided assembly line balancing problem with walking times and to propose the implementation of bees algorithm and Artificial Bee Colony algorithm due to the NP-hardness of the problem. An extensive computational study is also carried out and the comparative results are presented. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Parallel two-sided assembly line balancing problem Walking times bees algorithm Artificial bee colony algorithm Mathematical programming model

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Bee colony intelligence in zone constrained two-sided assembly line balancing problem

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EXPERT SYSTEMS WITH APPLICATIONS 2011年第9期38卷 11947-11957页

作者： Ozbakir, Lale Tapkan, Pinar Erciyes Univ Dept Ind Engn Kayseri Turkey

bees algorithm is a relatively new member of swarm intelligence based meta-heuristics which tries to model natural behavior of real 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 search algorithms for solving optimization problems in operational research. On the other hand, two-sided assembly lines are generally occurred in assembly of large-sized products such as buses and trucks. In a two-sided assembly line, different assembly tasks are carried out on the same product in parallel to both left and right sides of the line. In this study bees algorithm is adopted to solve two-sided assembly line balancing problem with zoning constraint so as to minimize the number of stations for a given cycle time. An extensive computational study is carried out and the results are compared with the results of several algorithms from the literature with the results of exact solution approaches and several algorithms from the literature such as ant colony optimization, tabu search. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Assembly line balancing Two-sided assembly line Swarm intelligence bees algorithm

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Smart piezoelectric patch in non-linear beam: design, vibration control and optimal location

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TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL 2014年第1期36卷 131-144页

作者： Moradi, Abbas Shirazi, Kourosh H. Keshavarz, Masoud Falehi, Ali D. Moradi, Mosayeb Shahid Chamran Univ Dept Mech Engn Ahvaz Iran Islamic Azad Univ Dept Elect Engn Izeh Branch Izeh Iran Islamic Azad Univ Dept Elect Engn Damavand Branch Damavand Iran

In this paper, the concept of smart materials has been engaged in order to control and abate the vibrations of non-linear beams. In the meantime, flexural vibration of viscoelastic has been taken into account aimed at reinforcing the carbon nanotube beams. This theory has applied the viscoelastic model to draw out the classical viscoelastic Kelvin-Voigt model. Likewise, the Hamilton's principle has been employed to derive the non-linear differential equations of beam's motion as for the piezoelectric patches and also the multiple scales method has been engaged in order to solve the non-linear equation of system motion. A fuzzy controller has been desirably arranged in the piezoelectric actuator/sensor loop to reduce the forced vibrations for any arbitrary stimulation. Due to majestic efficiency of the bees algorithm (BA) in the solution of many different engineering problems, it has been engaged for this work. To ensure and confirm the robustness of the proposed approach, three different conditions of forced stimulation have been taken into account for the studied system. In all, the non-linear simulation results unveil the robust performance of the proposed approach based on the BA technique in the damping of the system's vibrations.

关键词： Vibration of non-linear beam fuzzy controller optimization bees algorithm smart piezoelectric patch vibration control Multiple Scales

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Solving Parameter Identification of Nonlinear Problems by Artificial Bee Colony algorithm

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MATHEMATICAL PROBLEMS IN ENGINEERING 2014年第1期2014卷 1-6页

作者： Talatahari, S. Mohaggeg, H. Najafi, Kh. Manafzadeh, A. Univ Tabriz Dept Civil Engn Tabriz Iran Azad Univ Mahabad Dept Civil Engn Mahabad Iran

A new optimization method based on artificial bee colony (ABC) algorithm is presented for solving parameter identification problems. The ABC algorithm as a swarm intelligent optimization algorithm is inspired by honey bee foraging. In this paper, for the first time, the ABC method is developed to determine the optimum parameters of Bouc-Wen hysteretic systems. The proposed method exhibits efficiency, robustness, and insensitivity to noise-corrupted data. The results of the ABC are compared with those other optimization algorithms from the literature to show the efficiency of this technique for solving parameter identification problems.

关键词： PARAMETER identification NUMERICAL solutions for nonlinear theories bees algorithm PARTICLE swarm optimization ROBUST control

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FPGA-Based Bee Counter System

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IEEE ACCESS 2024年 12卷 30362-30381页

作者： Quiles-Latorre, Francisco J. Ortiz-Lopez, Manuel Rodriguez-Lozano, Francisco J. Brox, M. Flores, Jose M. Univ Cordoba Dept Elect & Comp Engn Cordoba 14071 Spain Univ Cordoba Dept Zool Campus Rabanales Cordoba 14071 Spain

The bee counter described in this paper is a device that is installed at the entrance of the hive and forces the bees to pass through one of its twenty passageways. Each passageway has an LED at the top, which emits infrared light, and at the bottom a double photodiode integrated in the same package, which generates electrical pulses when the bee passes through the passageway and cuts the light beam. The pulses are monitored by an FPGA that counts the number of bees entering and leaving the passageway, each of which has its own control unit, implemented in the FPGA, achieving a correct and independent interpretation of the temporal relationship between the two pulses. Furthermore, the sampling frequency of the pulses and the small distance between the photodiodes, because they are in the same encapsulation, make it possible to detect the input or output of bees moving very close to each other, with a minimum distance of approximately 1 mm. In addition, the fact that each passageway has its own control unit makes it possible to detect anomalous conditions due to a failure in the LED or photodiodes, or anomalies caused even by the bees as the propolis. For these cases, a timer associated to each passageway in the FPGA has been included, which starts a timer when one of the two photodiodes does not detect a light beam. The counter has two working modes: connected to a host or in stand-alone mode, in which it periodically sends the bee count. The counter has an UART of ABR (Automatic Baud Rate) type where it receives the AT commands sent by the host to request the input and output counts and the status of the passageways. The answer data corresponding to the command are also sent to the host through the UART. The FPGA description has been performed in VHDL and customizable so that it can be implemented for any number of passageways on any FPGA. The system was evaluated in three hives from August 2nd to September 23rd, 2020, during the end of the summer season and the pr

关键词： Monitoring Field programmable gate arrays Radar tracking Cameras Proposals Maintenance engineering Task analysis bees algorithm Instrumentation and measurement Beekeeping bee monitoring field programmable gate arrays instrumentation and measurement

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A Novel Deep Learning Framework With Meta-Heuristic Feature Selection for Enhanced Remote Sensing Image Classification

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IEEE ACCESS 2024年 12卷 91974-91998页

作者： Ahmed, Bilal Akram, Tallha Rameez Naqvi, Syed Alsuhaibani, Anas Altherwy, Youssef N. Masud, Usman COMSATS Univ Islamabad Dept Elect & Comp Engn Wah Campus Rawalpindi 47040 Pakistan Prince Sattam bin Abdulaziz Univ Coll Comp Engn & Sci Dept Informat Syst Al Kharj 11942 Saudi Arabia Univ Kassel Dept Elect Commun Engn D-34127 Kassel Germany

We propose a novel deep learning architecture, called XcelNet17, for image classification in remote sensing. Comprising fourteen convolutional and three fully connected layers, XcelNet17 outperforms several benchmark architectures available in the literature in terms of classification accuracy. Additionally, we present BA-ABC, a new hybrid feature selection algorithm that inherits the strengths of the Bat algorithm (BA) and the Artificial Bee Colony (ABC) algorithm. Together these contributions significantly enhance the performance and accuracy of remote sensing image classification tasks. The proposed framework is thoroughly trained and verified using five benchmark datasets typically used for remote sensing image classification, namely AID, RSSCN7, SIRI-WHU, UC Merced, and WHU RS-19. Our simulation results suggest that in terms of classification accuracy, XcelNet17 outperforms most of the well established networks including AlexNet, VGG16, VGG19, ResNet50, and DarkNet19 by obtaining accuracy values in the range of 94.6% and 99.9%. Furthermore, the proposed features selection method, when integrated with XcelNet17, yields much improved classification accuracy in comparison to various benchmarks including WOA, GWO, BA, ABC, and ACO algorithms. For example, an 8% superior performance on WHU-RS19 dataset has been observed. The attained results are further validated by an in-depth statistical analysis.

关键词： Image classification Classification algorithms Feature extraction Accuracy Remote sensing Convolutional neural networks Benchmark testing bees algorithm Artificial bee colony bat algorithm bio-inspired feature selection CNN architecture image classification remote sensing

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A MULTI-OBJECTIVE APPROACH TO THE ASSIGNMENT OF STOCK KEEPING UNITS TO UNIDIRECTIONAL PICKING LINES

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SOUTH AFRICAN JOURNAL OF INDUSTRIAL ENGINEERING 2017年第1期28卷 190-209页

作者： le Roux, G. J. Visagie, S. E. Univ Stellenbosch Dept Logist Stellenbosch South Africa

An order picking system in a distribution centre consisting of parallel unidirectional picking lines is considered. The objectives are to minimise the walking distance of the pickers, the largest volume of stock on a picking line over all picking lines, the number of small packages, and the total penalty incurred for late distributions. The problem is formulated as a multi-objective multiple knapsack problem that is not solvable in a realistic time. Population-based algorithms, including the artificial bee colony algorithm and the genetic algorithm, are also implemented. The results obtained from all algorithms indicate a substantial improvement on all objectives relative to historical assignments. The genetic algorithm delivers the best performance.

关键词： PICKERS (Weaving) STOCKS (Finance) bees algorithm GENETIC algorithms PROBLEM solving

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