Assembly sequence planning (ASP) known as a hard combinatorial optimization problem is an important part of assembly process planning. Determining the sequence of assembly arguably is quite challenging in ASP problem....
详细信息
ISBN:
(纸本)9781614994343;9781614994336
Assembly sequence planning (ASP) known as a hard combinatorial optimization problem is an important part of assembly process planning. Determining the sequence of assembly arguably is quite challenging in ASP problem. A good assembly sequence can help to reduce the cost and time of the manufacturing process. This paper presents an implementation of binary gravitational search algorithm (BGSA) for solving an assembly sequence planning (ASP) problem. Initially, each agent is represented by a feasible assembly sequence according to a precedence matrix. Next, binary gravitational search algorithm (BGSA) is used for updating the current to new feasible assembly sequence to solving ASP problem. Using a case study of ASP, the results show that the proposed approach based on BGSA is more efficient for solving the ASP problemin compare to other approaches based on simulated annealing (SA), genetic algorithm (GA), and binary particle swarm optimization (BPSO).
With the emergence of energy crisis and environmental pollution, the concept of microgrid (MG) is receiving much attention today. The optimal operation scheduling is an important research topic in the field of MG. In ...
详细信息
ISBN:
(纸本)9781479950324
With the emergence of energy crisis and environmental pollution, the concept of microgrid (MG) is receiving much attention today. The optimal operation scheduling is an important research topic in the field of MG. In this paper, binary gravitational search algorithm (BGSA) is proposed to optimize the operation scheduling of MG dynamically, which includes dynamic optimal unit commitment and power dispatch. At first, according to the characteristics of MG operation and its internal relations between different time periods, a mathematical optimization model is established to achieve the least operation and environmental cost, while meeting the load demand and system operating requirements. In order to solve this complex optimal problem, BGSA is proposed to optimize the unit commitment and power dispatch of MG. The simulation results show that the proposed method has efficient performance in optimizing operation scheduling of MG dynamically, and thus can improve the technical level of MG operation for more economic and environmental benefits.
This paper addresses an autonomous facial expression recognition system using the feature selection approach of the Quantum-Inspired binary gravitational search algorithm (QIBGSA). The detection of facial features com...
详细信息
This paper addresses an autonomous facial expression recognition system using the feature selection approach of the Quantum-Inspired binary gravitational search algorithm (QIBGSA). The detection of facial features completely depends upon the selection of precise features. The concept of QIBGSA is a modified binary version of the gravitationalsearchalgorithm by mimicking the properties of quantum mechanics. The QIBGSA approach reduces the computation cost for the initial extracted feature set using the hybrid approach of Local binary patterns with Gabor filter method. The proposed automated system is a sequential system with experimentation on the image-based dataset of Karolinska Directed Emotional Faces (KDEF) containing human faces with seven different emotions and different yaw angles. The experiments are performed to find out the optimal emotions using the feature selection approach of QIBGSA and classification using a deep convolutional neural network for robust and efficient facial expression recognition. Also, the effect of variations in the yaw angle (front to half side view) on facial expression recognition is studied. The results of the proposed system for the KDEF dataset are determined in three different cases of frontal view, half side view, and combined frontal and half side view images. The system efficacy is analyzed in terms of recognition rate.
The detection of variables that contribute to the variation of a system is one of the most important considerations in the industrial manufacturing processes. This work presents the combination of Mahalanobis-Taguchi ...
详细信息
The detection of variables that contribute to the variation of a system is one of the most important considerations in the industrial manufacturing processes. This work presents the combination of Mahalanobis-Taguchi system and a hybrid binary metaheuristic based on particle swarm optimization and gravitationalsearchalgorithm (BPSOGSA) to perform an optimal feature selection in order to detect the relevant variables in a real process of foam injection in automotive industry. The proposed method is compared with other feature selection approach based in binary PSO algorithm. The experimental results revealed that BPSOGSA is faster and successfully converge selecting a smallest subset of features than BPSO. Moreover, the feature selection effect is validated through other widely used machine learning algorithms which improve their accuracy performance when they are trained with the subset of detected variables by the proposed system.
作者：
AshaUniv Delhi
Bhaskaracharya Coll Appl Sci Dept Comp Sci Sect 2Phase 1 New Delhi 110075 India
The optimization of the problems significantly improves the solution of the complex problems. The reduction in the feature dimensionality is enormously salient to reduce the redundant features and improve the system a...
详细信息
The optimization of the problems significantly improves the solution of the complex problems. The reduction in the feature dimensionality is enormously salient to reduce the redundant features and improve the system accuracy. In this paper, an amalgamation of different concepts is proposed to optimize the features and improve the system classification. The experiment is performed on the facial expression detection application by proposing the amalgamation of deep neural network models with the variants of the gravitationalsearchalgorithm. Facial expressions are the movement of the facial components such as lips, nose, eyes that are considered as the features to classify human emotions into different classes. The initial feature extraction is performed with the local binary pattern. The extracted feature set is optimized with the variants of gravitationalsearchalgorithm (GSA) as standard gravitationalsearchalgorithm (SGSA), binary gravitational search algorithm (BGSA) and fast discrete gravitationalsearchalgorithm (FDGSA). The deep neural network models of deep convolutional neural network (DCNN) and extended deep convolutional neural network (EDCNN) are employed for the classification of emotions from imagery datasets of JAFFE and KDEF. The fixed pose images of both the datasets are acquired and comparison based on average recognition accuracy is performed. The comparative analysis of the mentioned techniques and state-of-the-art techniques illustrates the superior recognition accuracy of the FDGSA with the EDCNN technique.
Distribution system utilities attempt to minimize cost with consideration of the system performance improvement. This paper employs the network reconfiguration and capacitor placement simultaneously to reduce energy l...
详细信息
Distribution system utilities attempt to minimize cost with consideration of the system performance improvement. This paper employs the network reconfiguration and capacitor placement simultaneously to reduce energy losses and improve the system reliability subjected to satisfy operational and power quality constraints using a fuzzy approach. With respect to discrete and non-linear nature of the optimization problem, a binary gravitational search algorithm (BGSA) is utilized to solve the fuzzy multi-objective problem efficiently. The fast harmonic analysis method is used to perform harmonic power flow in the presence of shunt capacitors and non-linear loads. The state enumeration method based on Weibull-Markov stochastic model of the system components is adopted to assess reliability of different system configurations. Moreover, a new encoding strategy is proposed to boost the performance of network reconfiguration procedure. The IEEE 33-bus and an 83-bus practical distribution network of Taiwan Power Company (TPC) with a number of harmonic generating loads are utilized to test and validate the proposed method, and results are compared with binary Particle Swarm Optimization (BPSO) algorithm and binary Genetic algorithm (BGA). (C) 2014 Elsevier Ltd. All rights reserved.
Technological progresses in the gas sensor fields provide the possibility of designing and construction of Electronic nose (E-nose) based on the Biological nose. E-nose uses specific hardware and software units;Sensor...
详细信息
Technological progresses in the gas sensor fields provide the possibility of designing and construction of Electronic nose (E-nose) based on the Biological nose. E-nose uses specific hardware and software units;Sensor array is one of the critical units in the E-nose and its types of sensors are determined based on the application. So far, many achievements have been reported for using the E-nose in different fields of application. In this work, an E-nose for handling multi-purpose applications is proposed, and the employed hardware and pattern recognition techniques are depicted. To achieve higher recognition rate and lower power consumption, the improved binary gravitational search algorithm (IBGSA) and the K-nearest neighbor (KNN) classifier are used for automatic selecting the best combination of the sensors. The designed E-nose is tested by classifying the odors in different case studies, including moldy bread recognition in food and beverage field, herbs recognition in the medical field, and petroleum products recognition in the industrial field. Experimental results confirm the efficiency of the proposed method for E-nose realization.
Evolutionary algorithms start with an initial population vector, which is randomly generated when no preliminary knowledge about the solution is available. Recently, it has been claimed that in solving continuous doma...
详细信息
Evolutionary algorithms start with an initial population vector, which is randomly generated when no preliminary knowledge about the solution is available. Recently, it has been claimed that in solving continuous domain optimization problems, the simultaneous consideration of randomness and opposition is more effective than pure randomness. In this paper it is mathematically proven that this scheme, called opposition-based learning, also does well in binary spaces. The proposed binary opposition-based scheme can be embedded inside many binary population-based algorithms. We applied it to accelerate the convergence rate of binary gravitational search algorithm (BGSA) as an application. The experimental results and mathematical proofs confirm each other. (C) 2014 Elsevier B.V. All rights reserved.
A wide area measurement system installation cost minimisation and observability maximisation using binary gravitational search algorithm have been reported. Various methods have been employed in the past to determine ...
详细信息
A wide area measurement system installation cost minimisation and observability maximisation using binary gravitational search algorithm have been reported. Various methods have been employed in the past to determine the optimal locations of devices to retain the observability of the system. However, the costs of communication infrastructure (CI) from phasor data concentrator to phasor measurement units (PMUs) have not been given proper attention. To address this issue, the PMU placement problem has been formulated incorporating the cost of CI also in this study. Contingency cases have also been included to improve the reliability of the system. Besides, the effects of the presence of preinstalled PMUs have been considered. The results obtained for IEEE 14-bus, 30-bus and 118-bus systems have been compared with other methods in the literature. The test results reveal that the proposed methodology produced the PMU locations with higher observability and lesser distance path of establishing communication link compared to an existing method.
暂无评论