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Robust Parallel Machine Scheduling Problem with Uncertainties and Sequence-Dependent Setup Time

SCIENTIFIC PROGRAMMING 2016年第1期2016卷 1-13页

作者： Hu, Hongtao Ng, K. K. H. Qin, Yichen Shanghai Maritime Univ Logist Engn Coll Shanghai Peoples R China Hong Kong Polytech Univ Dept Ind & Syst Engn Hong Kong Hong Kong Peoples R China

A parallel machine scheduling problem in plastic production is studied in this paper. In this problem, the processing time and arrival time are uncertain but lie in their respective intervals. In addition, each job must be processed together with a mold while jobs which belong to one family can share the same mold. Therefore, time changing mold is required for two consecutive jobs that belong to different families, which is known as sequence-dependent setup time. This paper aims to identify a robust schedule by min-max regret criterion. It is proved that the scenario incurring maximal regret for each feasible solution lies in finite extreme scenarios. A mixed integer linear programming formulation and an exact algorithm are proposed to solve the problem. Moreover, a modified artificial bee colony algorithm is developed to solve large-scale problems. The performance of the presented algorithm is evaluated through extensive computational experiments and the results show that the proposed algorithm surpasses the exact method in terms of objective value and computational time.

关键词： PRODUCTION scheduling PLASTICS industries LINEAR programming bees algorithm PROBLEM solving

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Investigation on the Inversion of the Atmospheric Duct Using the Artificial Bee Colony algorithm Based on Opposition-Based Learning

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INTERNATIONAL JOURNAL OF ANTENNAS AND PROPAGATION 2016年第4-18期2016卷 2749035-2749035页

作者： Yang, Chao Zhang, Jian-Ke Guo, Li-Xin Xian Univ Posts & Telecommun Sch Sci Xian 710121 Peoples R China Xidian Univ Sch Phys & Optoelect Engn Xian 710071 Peoples R China

The artificial bee colony (ABC) algorithm is a recently introduced optimization method in the research field of swarm intelligence. This paper presents an improved ABC algorithm named as OGABC based on opposition-based learning (OBL) and global best search equation to overcome the shortcomings of the slow convergence rate and sinking into local optima in the process of inversion of atmospheric duct. Taking the inversion of the surface duct using refractivity from clutter (RFC) technique as an example to validate the performance of the proposed OGABC, the inversion results are compared with those of the modified invasive weed optimization (MIWO) and ABC. The radar sea clutter power calculated by parabolic equation method using the simulated and measured refractivity profile is utilized to carry out the inversion of the surface duct, respectively. The comparative investigation results indicate that the performance of OGABC is superior to that of MIWO and ABC in terms of stability, accuracy, and convergence rate during the process of inversion.

关键词： Atmospheric electromagnetic wave propagation bees algorithm Swarm intelligence Clutter (Radar) Mathematical optimization

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Combinational Circuit Design Using bees algorithm

Combinational Circuit Design Using Bees Algorithm

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2011 International Conference on Intelligent Computing and Integrated Systems(ICISS 2011)

作者： Nahid Mollabakhshi Mohammad Eshghi Department of Computer Engineering Science and Research Branch Islamic Azad UniversityTehran Iran ECE department Shahid Beheshti UniversityTehran Iran

In this paper a novel method to designingcombinational circuits using bees algorithm is presented. Inautomatic evolutionary design methods, the main problem isrelated to "combinatorial explosion" existing in those *** evolutionary design methods are based on "generate andtest" model, therefore with growing input numbers of digitalcircuits, the number of potential combinations which must betested are growing exponentially. To solve this problem, it isimportant to elaborate efficient decomposition techniques of thedesigned circuits to some less complex sub-circuits, and then todesign each of them independently. We present a new applicationof bees algorithm, and design and optimize combinational circuits.A computer simulation is developed to verify the performance ofthe proposed algorithm. We compared the circuits obtained by ourproposed system to the circuits designed by experienced humandesigners. In comparison to human design, our automated designshad fewer gates.

关键词： bees algorithm combinational digital circuit evolutionary algorithm

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Efficient load balancing using the bees algorithm 11

Efficient load balancing using the bees algorithm

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Proceedings of the 24th international conference on Industrial engineering and other applications of applied intelligent systems conference on Modern approaches in applied intelligence - Volume Part II

作者： Anabela Moreira Bernardino Eugénia Moreira Bernardino Juan Manuel Sánchez-Pérez Juan Antonio Gómez-Pulido Miguel Angel Vega-Rodríguez Computer Science and Communication Research Centre School of Technology and Management Polytechnic Institute of Leiria Leiria Portugal Department of Technologies of Computers and Communications Polytechnic School University of Extremadura Cáceres Spain

ISBN: (纸本)9783642218262

The massive growth of the Internet traffic in the last decades has motivated the design of high-speed optical networks. Resilient Packet Ring (RPR), also known as IEEE 802.17, is a standard designed for optimising the transport of data traffic over optical fiber ring networks. In this paper, we consider a Weighted Ring Arc-Loading Problem (WRALP), which arises in engineering and planning of the RPR systems. The WRALP is a combinatorial optimisation NP-complete problem. Given a set of point-to-point unidirectional traffic demands of a specified bandwidth, the demands should be assigned to the clockwise or to the counter-clockwise ring in order to yield the best performance. This paper suggests an efficient load balancing algorithm - the bees algorithm. We compare our results with nine meta-heuristics used in literature to solve the same problem. The simulation results verify the effectiveness and robustness of the bees algorithm.

关键词： bees algorithm

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Crack identification in post-buckled beam-type structures

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SMART STRUCTURES AND SYSTEMS 2015年第5期15卷 1233-1252页

作者： Moradi, Shapour Moghadam, Peyman Jamshidi Shahid Chamran Univ Dept Mech Engn Ahvaz 61357 Iran Dept Mech Engn Mech Engn Mahshahr 63518 Iran

This study investigates the problem of crack detection in post-buckled beam-type structures. The beam under the axial compressive force has a crack, assumed to be open and through the width. The crack, which is modeled by a massless rotational spring, divides the beam into two segments. The crack detection is considered as an optimization problem, and the weighted sum of the squared errors between the measured and computed natural frequencies is minimized by the bees algorithm. To find the natural frequencies, the governing nonlinear equations of motion for the post-buckled state are first derived. The solution of the nonlinear differential equations of the two segments consists of static and dynamic parts. The differential quadrature method along with an arc length strategy is used to solve the static part, while the same method is utilized for the solution of the linearized dynamic part and the extraction of the natural frequencies of the cracked beam. The investigation includes several numerical as well as experimental case studies on the post-buckled simply supported and clamped-clamped beams having open cracks. The results show that several parameters such as the amount of applied compressive force and boundary conditions influences the outcome of the crack detection scheme. The identification results also show that the crack position and depth can be predicted well by the presented method.

关键词： crack detection beam vibration postbuckling differential quadrature method bees algorithm

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Design Optimization Comparison of BLPM Traction Motor using bees and Genetic algorithms

Design Optimization Comparison of BLPM Traction Motor using ...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Braiwish, N. Y. Anayi, F. J. Fahmy, A. A. Eldukhri, E. E. Cardiff Univ Sch Engn Wolfson Ctr Magnet Cardiff CF10 3AX S Glam Wales Cardiff Univ Inst Mech & Mfg Engn Cardiff CF10 3AX S Glam Wales

ISBN: (纸本)9781479978007

Electric machines designs for traction applications are concerned with high power density, high efficiency and low manufacturing cost. In order to achieve better combination of parameters that satisfy the machine electromagnetics, mechanical, and thermal designs limitations;an optimization algorithm is very necessary. Therefore;this work focuses on comparing two optimization algorithms that are utilized to search for optimal solution to design Brushless Permanent Magnet (BLPM) Motor. The target machine design has to meet with FReedomCAR specifications as detailed by UQM Technologies Inc. In this paper, a relatively new modern evolutionary optimization technique known as the bees algorithm (BA) employed to search for the optimum design parameters according to a pre-defined multiobjective function. The results from BA have been compared with the other results obtained from Genetic algorithm (GA). Therefore, both optimization methods have been compared in terms of computational efficiency and ability to find optimal solution for BLPM. However, the comparison results show that BA has better computational ability to search for optimal parameters and achieves lower average value for the objective function than the GA.

关键词： bees algorithm Brushless Permanent Magnet Motor BLPM Genetic algorithm fitness value Multi-objective function

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A Novel Artificial Bee Colony algorithm for Function Optimization

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

作者： Zhang, Song Liu, Sanyang Xidian Univ Sch Math & Stat Xian 710071 Peoples R China

It is known that both exploration and exploitation are important in the search equations of ABC algorithms. How to well balance the two abilities in the search process is still a challenging problem in ABC algorithms. In this paper, we propose a novel artificial bee algorithm named as "NABC," by incorporating the information of the global best solution into the solution search equation of the onlookers stage to improve the exploitation. At the same time, we improve the search equation of the employed bees to keep the exploration. The experimental results of NABC tested on a set of 11 numerical benchmark functions show good performance and fast convergence in solving function optimization problems, compared with variant ABC, DE, and PSO algorithms. The application of NABC on solving five standard knapsack problems shows its effectiveness and practicability.

关键词： ARTIFICIAL intelligence bees algorithm NUMERICAL analysis STOCHASTIC convergence PROBLEM solving

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Quaternion-Based Improved Artificial Bee Colony algorithm for Color Remote Sensing Image Edge Detection

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MATHEMATICAL PROBLEMS IN ENGINEERING 2015年第1期2015卷 p1-10页

作者： Liu, Dujin Wang, Huajun Wang, Sen Pu, Guolin Deng, Xiaoya Hou, Xiang Chengdu Univ Technol Coll Geophys Chengdu 610059 Peoples R China Sichuan Univ Arts & Sci Sch Comp Sci Dazhou 635000 Peoples R China China Acad Telecommun Technol State Key Lab Wireless Mobile Commun Beijing 100191 Peoples R China

As the color remote sensing image has the most notable features such as huge amount of data, rich image details, and the containing of too much noise, the edge detection becomes a grave challenge in processing of remote sensing image data. To explore a possible solution to the urgent problem, in this paper, we first introduced the quaternion into the representation of color image. In this way, a color can be represented and analyzed as a single entity. Then a novel artificial bee colony method named improved artificial bee colony which can improve the performance of conventional artificial bee colony was proposed. In this method, in order to balance the exploration and the exploitation, two new search equations were presented to generate candidate solutions in the employed bee phase and the onlookers phase, respectively. Additionally, some more reasonable artificial bee colony parameters were proposed to improve the performance of the artificial bee colony. Then we applied the proposed method to the quaternion vectors to perform the edge detection of color remote sensing image. Experimental results show that our method can get a better edge detection effect than other methods.

关键词： QUATERNIONS bees algorithm REMOTE sensing IMAGE converters EDGE detection (Image processing) COLOR image processing

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Polygonal Approximation Using an Artificial Bee Colony algorithm

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

作者： Huang, Shu-Chien Natl Pingtung Univ Dept Comp Sci Pingtung City 90003 Taiwan

A polygonal approximation method based on the new artificial bee colony (NABC) algorithm is proposed in this paper. In the present method, a solution is represented by a vector, and the objective function is defined as the integral square error between the given curve and its corresponding polygon. The search process, including the employed bee stage, the onlooker bee stage, and the scout bee stage, has been constructed for this specific problem. Most experiments show that the present method when compared with the DE-based method can obtain superior approximation results with less error norm with respect to the original curves.

关键词： POLYGONS APPROXIMATION theory bees algorithm INTEGRALS VECTOR analysis COMPUTER science

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Artificial Bee Colony Optimizer with Bee-to-Bee Communication and Multipopulation Coevolution for Multilevel Threshold Image Segmentation

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MATHEMATICAL PROBLEMS IN ENGINEERING 2015年第1期2015卷 1-23页

作者： Li, Jun-yi Zhao, Yi-ding Li, Jian-hua Liu, Xiao-jun Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn Shanghai 200230 Peoples R China Zhongyuan Univ Technol Sch Comp Sci Zhengzhou Peoples R China Jilin Univ Zhuhai Coll Dept Logist & Informat Management Zhuhai Peoples R China

This paper proposes a modified artificial bee colony optimizer (MABC) by combining bee-to-bee communication pattern and multipopulation cooperative mechanism. In the bee-to-bee communication model, with the enhanced information exchange strategy, individuals can share more information from the elites through the Von Neumann topology. With the multipopulation cooperative mechanism, the hierarchical colony with different topologies can be structured, which can maintain diversity of the whole community. The experimental results on comparing the MABC to several successful EA and SI algorithms on a set of benchmarks demonstrated the advantage of the MABC algorithm. Furthermore, we employed the MABC algorithm to resolve the multilevel image segmentation problem. Experimental results of the new method on a variety of images demonstrated the performance superiority of the proposed algorithm.

关键词： bees algorithm COEVOLUTION SEGMENTATION (Image processing) THRESHOLDING algorithms INFORMATION sharing PERFORMANCE evaluation

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