In the transportation service, customers' specially ordered time window is not always strictly obeyed and deviation of service time from customer-ordered time window determine customers' satisfaction degree, which c...In the transportation service, customers' specially ordered time window is not always strictly obeyed and deviation of service time from customer-ordered time window determine customers' satisfaction degree, which can be quantified by satisfactory function. And improved saving algorithm is proposed to solve the multi-objective model. A case study is also presented to verify effectiveness of the proposed algorithm.展开更多
A new local cost function is proposed in this paper based on the linear relationship assumption between the values of the color components and the intensity component in each local image window,then a new quadratic ob...A new local cost function is proposed in this paper based on the linear relationship assumption between the values of the color components and the intensity component in each local image window,then a new quadratic objective function is derived from it and the globally optimal chrominance values can be computed by solving a sparse linear system of equations.Through the colorization experiments on various test images,it is confirmed that the colorized images obtained by our proposed method have more vivid colors and sharper boundaries than those obtained by the traditional method.The peak signal to noise ratio(PSNR) of the colorized images and the average estimation error of the chrominance values relative to the original images also show that our proposed method gives more precise estimation than the traditional method.展开更多
文摘In the transportation service, customers' specially ordered time window is not always strictly obeyed and deviation of service time from customer-ordered time window determine customers' satisfaction degree, which can be quantified by satisfactory function. And improved saving algorithm is proposed to solve the multi-objective model. A case study is also presented to verify effectiveness of the proposed algorithm.
基金Supported by the National Natural Science Foundation of China(No.61073089)the Joint Funds of the National Natural Science,Foundation of China(No.U1304616)the Qinhuangdao Research&Development Program of Science&Technology(No.2012021A044)
文摘A new local cost function is proposed in this paper based on the linear relationship assumption between the values of the color components and the intensity component in each local image window,then a new quadratic objective function is derived from it and the globally optimal chrominance values can be computed by solving a sparse linear system of equations.Through the colorization experiments on various test images,it is confirmed that the colorized images obtained by our proposed method have more vivid colors and sharper boundaries than those obtained by the traditional method.The peak signal to noise ratio(PSNR) of the colorized images and the average estimation error of the chrominance values relative to the original images also show that our proposed method gives more precise estimation than the traditional method.