In this paper, the environment heterogeneous fixed fleet vehicle routing problem with time windows (EHFFVRP-TW) has been proposed. The model added the carbon emission factor and time windows based on the heterogeneous...
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ISBN:
(纸本)9783319410098;9783319410081
In this paper, the environment heterogeneous fixed fleet vehicle routing problem with time windows (EHFFVRP-TW) has been proposed. The model added the carbon emission factor and time windows based on the heterogeneous fixed fleet vehicle routing problem (HFFVRP) where we consider the cost benefit of carbon trading by selling or purchasing the carbon emission rights. comprehensive learning particle swarm optimization (CLPSO) is presented to solve the model, and the performance of CLPSO is estimated by comparing with PSO and GA. We adopt binary encoding way and set 2N dimension of particle to correspond the customer. The first N dimensional coding represents the vehicle number which visited the customer. And the last N dimensional coding correspond to the path order of vehicle. In the experiment, it's demonstrated CLPSO performs best compared with other two algorithm. CLPSO has improved the shortage of premature convergence in PSO and showed the advantages of getting lower cost and better routing.
In this work, we propose a comprehensive learning particle swarm optimization (CLPSO) based weighted clustering algorithm for mobile ad hoc networks. It finds the optimal number of clusters to efficiently manage the r...
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ISBN:
(纸本)9783642108433
In this work, we propose a comprehensive learning particle swarm optimization (CLPSO) based weighted clustering algorithm for mobile ad hoc networks. It finds the optimal number of clusters to efficiently manage the resources of the network. The proposed CLPSO based clustering algorithm takes into consideration the ideal degree, transmission power, mobility, and battery power of the mobile nodes. A weight is assigned to each of these parameters of the network. Each particle contains information about the cluster-heads and the members of each cluster. The simulation results are compared with two other well-known clustering algorithms. Results show that the proposed technique works better than the other techniques especially in dense networks.
作者：
Zhang, QianWang, QunjingLi, GuoliAnhui Univ
Sch Elect Engn & Automat Hefei 230039 Peoples R China Anhui Univ
Engn Res Ctr Power Qual Minist Educ Hefei 230039 Peoples R China Anhui Univ
Natl Engn Lab Energy Saving Motor & Control Techn Hefei 230039 Peoples R China
The servo turntable is an essential part of radar antenna, plays an important role for the accuracy and smoothness of tracking. There are several working stations which is different from even running in the antenna se...
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ISBN:
(纸本)9781479983896
The servo turntable is an essential part of radar antenna, plays an important role for the accuracy and smoothness of tracking. There are several working stations which is different from even running in the antenna servo turntable, such as low-speeding, changing-over, acceleration or deceleration etc. In this paper, a kind of switched model is introduced to describe the relationship between input and output signals in complex working conditions for the turntable. Then the parameters identification of switched system is summarized as a Constrained Multi-Objective Problem (CMOP). Further, the comprehensive learning particle swarm optimization (CLPSO) is applied to the proposed CMOP to obtain a set of appropriate parameters. Finally, the simulation and quality of fitness calculation results demonstrate the precision of the switched model and effectiveness of the identification algorithm.
The servo turntable is an essential part of radar antenna, plays an important role for the accuracy and smoothness of tracking. There are several working stations which is different from even running in the antenna se...
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ISBN:
(纸本)9781479984671
The servo turntable is an essential part of radar antenna, plays an important role for the accuracy and smoothness of tracking. There are several working stations which is different from even running in the antenna servo turntable, such as lowspeeding, changing-over, acceleration or deceleration etc. In this paper, a kind of switched model is introduced to describe the relationship between input and output signals in complex working conditions for the turntable. Then the parameters identification of switched system is summarized as a Constrained Multi-Objective Problem (CMOP). Further, the comprehensive learning particle swarm optimization (CLPSO) is applied to the proposed CMOP to obtain a set of appropriate parameters. Finally, the simulation and quality of fitness calculation results demonstrate the precision of the switched model and effectiveness of the identification algorithm.
Frequent pattern mining has attracted much attention and wide applications owing to its simple concept and strategy. It is of the most important task in data mining and knowledge discovery. But usually a large number ...
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Frequent pattern mining has attracted much attention and wide applications owing to its simple concept and strategy. It is of the most important task in data mining and knowledge discovery. But usually a large number of frequent patterns get generated from a large scale of data matrix which is a time consuming affair. So, in order to discretize the data matrix a mathematical concept called fuzzy logic was used. It generalizes the data matrix values in the range of 0 to 1. In the due course of time, an evolutionary algorithm, called particleswarmoptimization (PSO) has also gained much popularity. But due to the premature convergence of PSO, a comprehensivelearning strategy was introduced that used all particles’ best information to update a particle's velocity. It also enabled the diversity of the swarm to be preserved to discourage premature convergence. In this paper, frequent patterns were generated from the fuzzy dataset (data matrix converted into fuzzy data matrix) using the Frequent Pattern (FP) growth algorithm. In order to generate some of the best individual frequent patterns out of the entire set of patterns, the CLPSO algorithm was used with a selection measure called mean squared residue (MSR) score. It was noted that the CLPSO algorithm outperformed the traditional PSO algorithm in the generation of the best individual patterns with a comparatively lower MSR value.
optimization of a nonuniformly slotted rectangular waveguide antenna is performed using comprehensive learning particle swarm optimization (CLPSO) for the design of a high-efficiency, low-sidelobe antenna with a cosec...
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optimization of a nonuniformly slotted rectangular waveguide antenna is performed using comprehensive learning particle swarm optimization (CLPSO) for the design of a high-efficiency, low-sidelobe antenna with a cosecant-squared beam. Mode-snatching method and the Fourier transform are used to analyze the nonuniformly slotted rectangular waveguide. The computational results show that the proposed optimizer with a fast convergent series solver is useful for the design and optimization of nonuniform slot arrays. (C) 2008 Wiley Periodicals, Inc.
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