In solving multi-objective vehicle routing problems with time windows (MOVRPTW),most existing algorithms focus on the optimization of a single problem formulation. However,little effort has been devoted to exploiting ...
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In solving multi-objective vehicle routing problems with time windows (MOVRPTW),most existing algorithms focus on the optimization of a single problem formulation. However,little effort has been devoted to exploiting valuable knowledge from the alternate formulations of MOVRPTW for better optimization performance. Aiming at this insufficiency,this study proposes a decomposition-based multi-objective multiform evolutionary algorithm (MMFEA/D),which performs the evolutionary search on multiple alternate formulations of MOVRPTW simultaneously to complement each other. In particular,the main characteristics of MMFEA/D are three folds. First,a multiform construction (MFC) strategy is adopted to construct multiple alternate formulations,each of which is formulated by grouping several adjacent subproblems based on the decomposition of MOVRPTW. Second,a transfer reproduction (TFR) mechanism is designed to generate offspring for each formulation via transferring promising solutions from other formulations,making that the useful traits captured from different formulations can be shared and leveraged to guide the evolutionary search. Third,an adaptive local search (ALS) strategy is developed to invest search effort on different alternate formulations as per their usefulness for MOVRPTW,thus facilitating the efficient allocation of computational resources. Experimental studies have demonstrated the superior performance of MMFEA/D on the classical Solomon instances and the real-world instances.
Large language models (LLMs) possess extensive prior knowledge and powerful in-context learning (ICL) capabilities, presenting significant opportunities for low-resource tasks. Though effective, several key issues sti...
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Media power,the impact that media have on public opinion and perspectives,plays a significant role in maintaining internal stability,exerting external influence,and shaping international dynamics for nations/***,prior...
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Media power,the impact that media have on public opinion and perspectives,plays a significant role in maintaining internal stability,exerting external influence,and shaping international dynamics for nations/***,prior research has primarily concentrated on news content and reporting time,resulting in limitations in evaluating media *** more accurately assess media power,we use news content,news reporting time,and news emotion simultaneously to explore the emotional contagion between *** use emotional contagion to measure the mutual influence between media and regard the media with greater impact as having stronger media *** propose a framework called Measuring Media Power via Emotional Contagion(MMPEC)to capture emotional contagion among media,enabling a more accurate assessment of media power at the media and national/regional *** also interprets experimental results through correlation and causality analyses,ensuring *** analyses confirm the higher accuracy of MMPEC compared to other baseline models,as demonstrated in the context of COVID-19-related news,yielding compelling and interesting insights.
With the recent advancement of the Internet of Things (IoT) and edge computing, there’s a surge in demand for effective intelligent data analytics, especially vision analysis. Neural network (NN) partitioning, an edg...
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Background: Collaborative Representation (CR) has been widely used in Single Image Super Resolution (SISR) with the assumption that Low-resolution (LR) and high-resolution (HR) features can be linearly represented by ...
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Arrhythmia is a serious cardiovascular disease that can greatly affect a patient’s health and even pose a risk to their life. Automatic classification of arrhythmia through 12-lead electrocardiogram (ECG) is of great...
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In recent years, as a means of identity authentication, the finger-vein pattern has gradually attracted widespread attention in the academia and industry due to its unique biological characteristics, high stability, a...
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In the field of saliency detection for panoramic images, traditional equirectangular and cube projection methods in panoramic image saliency detection often face issues like distortion and discontinuities, impacting d...
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Travel time estimation(TTE)is a fundamental task to build intelligent transportation ***,most existing TTE solutions design models upon simple homogeneous graphs and ignore the heterogeneity of traffic networks,where,...
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Travel time estimation(TTE)is a fundamental task to build intelligent transportation ***,most existing TTE solutions design models upon simple homogeneous graphs and ignore the heterogeneity of traffic networks,where,e.g.,main roads typically contribute differently from side *** terms of spatial dimension,few studies consider the dynamic spatial correlations across road segments,e.g.,the traffic speed/volume on road segment A may correlate with the traffic speed/volume on road segment B,where A and B could be adjacent or non-adjacent,and such correlations may vary across *** terms of temporal dimension,even fewer studies consider the dynamic temporal dependences,where,e.g.,the historical states of road A may directly correlate with the recent state of A,and may also indirectly correlate with the recent state of road *** track all aforementioned issues of existing TTE approaches,we provide HDTTE,a solution that employs heterogeneous and dynamic spatio-temporal predictive ***,we first design a general multi-relational graph constructor that extracts hidden heterogeneous information of road segments,where we model road segments as nodes and model correlations as edges in the multi-relational ***,we propose a dynamic graph attention convolution module that aggregates dynamic spatial dependence of neighbor roads to focal *** also present a novel correlation-augmented temporal convolution module to capture the influence of states at past time steps on current traffic ***,in view of the periodic dependence of traffic,we develop a multi-scale adaptive fusion layer to enable HDTTE to exploit periodic patterns from recent,daily,and weekly traffic *** experimental study using real-life highway and urban datasets demonstrates the validity of the approach and its advantage over others.
The indiscriminate distribution of a large number of unlicensed images through the Internet seriously harms the benefits of image owners, which prompts the study of image copyright protection solutions. Existing block...
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