15,100 research outputs found
Lun xi qu fan ying wei da qun zhong shi dai wen ti. v.1
No full text戲劇報編輯部戲曲硏究编委会编.附簡譜歌曲.Xi ju bao bian ji bu Xi qu yan jiu bian wei hui bian.Fu jian pu ge qu
Dataset for: Mid-infrared silicon-on-insulator waveguides with single-mode propagation over an octave of frequency
No full textExperimental and simulation data for the paper:
Callum J. Stirling, Wei Cao, Jamie D. Reynolds, Zhibo Qu, Thomas D. Bradley, Lorenzo Mastronardi, Frederic Y. Gardes, Goran Z. Mashanovich, Milos Nedeljkovic. (2021). Mid-infrared silicon-on-insulator wavegudes with single-mode propagation over an octave of frequency, Optics Express</span
1st AIROYoung PhD School and the 3rd AIROYoung Workshop "Advanced Methods in Optimization and Data Science"
No full textLast-mile logistics optimization in the on-demand economy
No full textL'abstract è presente nell'allegato / the abstract is in the attachmen
Wei liao yuan
No full text第1部. 情天刼 -- 第2部. 離亂曲 -- 第3部. 未了緣.俊人著.小說."本書共分三部: 1. 情天刼 ; 2. 離亂曲 ; 3. 未了緣"--T.p.第2部離亂曲缺p. 231-233.Junren zhu.Xiao shuo."Ben shu gong fen san bu: 1. Qing tian jie ; 2. Li luan qu ; 3. Wei liao yuan"--T.p.Di 2 bu Li luan qu que p. 231-233.Di 1 bu. Qing tian jie -- di 2 bu. Li luan qu -- di 3 bu. Wei liao yuan
Qu yuan zhuan
No full text陸時雍疏.綫裝, 1函.框20.9x14.7公分, 9行20字, 小字雙行同. 白口, 四周單邊, 無魚尾. 版心上鐫題名, 中鐫卷次及小題, 下鐫葉次及"緝柳齋藏版". 眉端刻評, 有批點.内封面鐫"檇李陸昭仲先生纂輯, 學山堂梓行"With: 讀楚辭語 / 陸時雍 ; 附錄楚辭雜論 ; 屈原傳.鈐"學山堂", "開卷有益"硃文印Xian zhuang, 1 han.Kuang 20.9 x 14.7 gong fen, 9 hang 20 zi, xiao zi shuang hang tong. Bai kou, si zhou dan bian, wu yu wei. Ban xin shang juan ti ming, zhong juan juan ci ji xiao ti, xia juan ye ci ji "Ji liu zhai cang ban". Mei duan ke ping, you pi dian.Nei feng mian juan "Zuili Lu Zhaozhong xian sheng zuan ji, Xue shan tang zi hang"Lu Shiyong shu.With: Du chu ci yu / Lu Shiyong ; Fu lu chu ci za lun ; Qu Yuan zhuan.Qian "Xue shan tang", "Kai juan you yi" zhu wen yi
Branch and price for the time-dependent green vehicle routing problem with time windows in real road network
No full text
A simulation-optimization approach for the management of the on-demand parcel delivery in sharing economy
No full textthe use of multiple delivery options and crowd drivers, reflecting the synchromodality in the urban context. We propose a multi-stage stochastic model, and we solve the problem by using a simulation-optimization strategy. It relies on a Monte Carlo simulation and a large neighborhood search (LNS) heuristic for optimization. We conduct a case study in the medium-sized city of Turin (Italy) to measure the potential impact of integrating cargo bikes and crowd drivers in parcel delivery. Experimental results show that combining crowd drivers and green carriers with the traditional van to manage the parcel delivery is beneficial in terms of economic and environmental cost-saving, while the operational efficiency decreases. Besides, the green carriers and crowd drivers are promising delivery options to deal with online customer requests in the context of stochastic and dynamic parcel delivery. The resulting set of policies are part of the outcomes of the Logistics and Mobility Plan 2019-2021 in the Piedmont region
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