Ant colony optimization (ACO) has been found to be useful on several vehicle routing problem variations. In this work, ACO is applied to the electric vehicle routing problem with time windows (E-VRPTW). The E-VRPTW ha...
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ISBN:
(纸本)9781665487696
Ant colony optimization (ACO) has been found to be useful on several vehicle routing problem variations. In this work, ACO is applied to the electric vehicle routing problem with time windows (E-VRPTW). The E-VRPTW has a hierarchical multiple objective function, which is to minimize the number of electric vehicles and the total distance traveled. A multiple ACO is applied to E-VRPTW in which two colonies cooperate to minimize the objectives in parallel. A local search is embedded in ACO to improve the quality of the output. The experimental results on a set of benchmark instances show that the multiple ACO is competitive with existing methods.
An optical fiber sensor with a single mode-multimode-single mode (SMS) structure is proposed to detect ethanol vapor ranging between 100–500 ppm via the evanescent field interaction at the interface between the optic...
An optical fiber sensor with a single mode-multimode-single mode (SMS) structure is proposed to detect ethanol vapor ranging between 100–500 ppm via the evanescent field interaction at the interface between the optical fiber and ethanol vapor. The proposed optical fiber sensor offers real-time and non-invasive monitoring of ethanol vapor, which is one of the biomarkers of diabetes. Molecular imprinted polymer (MIP) is coated at a multimode fiber region, which is considered to be a sensing area, to improve the selectivity of the ethanol biomarker. The sensor works based on wavelength interrogation by detecting the change in wavelength due to the change in vapor concentration. The fabricated sensor has a sensitivity of 0.0013 nm/ppm, which suggests the potential to be used as a monitoring device for breath analysis.
This paper considers distributed online nonconvex optimization with time-varying inequality constraints over a network of agents. For a time-varying graph, we propose a distributed online primal–dual algorithm with c...
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This paper investigates the cooperative output regulation (COR) of nonlinear multi-agent systems (MASs) with long input delay based on periodic event-triggered mechanism. Compared with other mechanisms, periodic event...
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Fitness landscape analysis (FLA) is quite important in evolutionary computation. In this paper, we propose a novel FLA method, the nearest-better network (NBN), which uses the nearest-better relationship to simplify t...
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Emissions from mobile sources and stationary sources contribute to atmospheric pollution in China,and its components,which include ultrafine particles(UFPs),volatile organic compounds(VOCs),and other reactive gases,su...
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Emissions from mobile sources and stationary sources contribute to atmospheric pollution in China,and its components,which include ultrafine particles(UFPs),volatile organic compounds(VOCs),and other reactive gases,such as NH3and NOx,are the most harmful to human *** has released various regulations and standards to address pollution from mobile and stationary ***,it is urgent to develop online monitoring technology for atmospheric pollution source *** study provides an overview of the main progress in mobile and stationary source monitoring technology in China and describes the comprehensive application of some typical instruments in vital areas in recent *** instruments have been applied to monitor emissions from motor vehicles,ships,airports,the chemical industry,and electric power *** only has the level of atmospheric environment monitoring technology and equipment been improving,but relevant regulations and standards have also been constantly ***,the developed instruments can provide scientific assistance for the successful implementation of *** to the potential problem areas in atmospheric pollution in China,some research hotspots and future trends of atmospheric online monitoring technology are ***,more advanced atmospheric online monitoring technology will contribute to a comprehensive understanding of atmospheric pollution and improve environmental monitoring capacity.
This study aims to apply Localized Surface Plasmon Resonance (LSPR), Maxwell Garnett's formula, and Fabry-Perot theory together to design and develop a LSPR enhanced gold colloidal nanoparticles (AuNPs) sensor to ...
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ISBN:
(数字)9781728187600
ISBN:
(纸本)9781728187617
This study aims to apply Localized Surface Plasmon Resonance (LSPR), Maxwell Garnett's formula, and Fabry-Perot theory together to design and develop a LSPR enhanced gold colloidal nanoparticles (AuNPs) sensor to be used in biomedical applications such as detection of glucose level in urine for early stage screening of diabetic patients. In this work, the LSPR based sensor has been designed and studied numerically to detect the glucose level from the change in the effective index resulting in a red shift of the absorption peak. The sensors were designed to have various sizes of the gold nanoparticles in a range between 20 nm and 100 nm by having different molar ratio with Trisodium Citrate (TSC) which acts as stabilizer in the synthesis. The maximum possible sensitivity of the sensor can be achieved with 70 nm diameter of gold nanoparticles at 0.2 volume fraction of AuNP to glucose solution.
Nonlinearity is ubiquitous in engineering and natural *** development of nonlinear control can be traced back to decades *** date,the research has reached the stage that emphasizes developing methodologies that can ha...
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Nonlinearity is ubiquitous in engineering and natural *** development of nonlinear control can be traced back to decades *** date,the research has reached the stage that emphasizes developing methodologies that can handle the complexity characterized by uncertainty,
Traditional programming method can achieve certain manipulation tasks with the assumption that robot environment is known and ***,with robots gradually applied in more domains,robots often encounter working scenes whi...
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Traditional programming method can achieve certain manipulation tasks with the assumption that robot environment is known and ***,with robots gradually applied in more domains,robots often encounter working scenes which are complicated,unpredictable,and *** overcome the limitation of traditional programming method,in this paper,we apply deep reinforcement learning(DRL) method to train robot agent to obtain skill *** policy trained with DRL on real-world robot is time-consuming and costly,we propose a novel and simple learning paradigm with the aim of training physical robot ***,our method train a virtual agent in an simulated environment to reach random target position from random initial ***,virtual agent trajectory sequence obtained with the trained policy,is transformed to real-world robot command with coordinate transformation to control robot performing reaching *** show that the proposed method can obtain self-adaptive reaching policy with low training cost,which is of great benefits for developing intelligent and robust robot manipulation skill system.
Parallelizing metaheuristics has become a common practice considering the computation power and resources available nowadays. The aim of parallelizing a metaheuristic is either to increase the quality of the generated...
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ISBN:
(数字)9781728124858
ISBN:
(纸本)9781728124865
Parallelizing metaheuristics has become a common practice considering the computation power and resources available nowadays. The aim of parallelizing a metaheuristic is either to increase the quality of the generated output, given a fixed computation time, or to reduce the required time in generating an output. In this work, we parallelize one of the best-performing ant colony optimization (ACO) algorithms and apply it to the electric vehicle routing problem (EVRP). EVRP is more challenging than the conventional vehicle routing problem, as with the consideration of electric vehicles additional hard constraints arise within the EVRP due to their limited driving range (e.g., the consideration whether electric vehicles need to visit a charging station during their daily operation). The proposed parallel ACO algorithm with several colonies also uses a migration policy to allow communication between the different colonies. From the simulation studies it is shown that parallelizing ACO algorithms, both with and without a migration policy, is highly effective.
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