In recent years, the frequent occurrence of public health emergencies has had a significant impact on people’s life. The study of emergency logistics has also attracted scholars’ attention. Therefore, matching emergency materials’ supply and demand quickly, which meets urgency and satisfaction, is the purpose of this paper. This paper used the Metabolism Grey Model (1,1) (GM (1,1)) and the material demand prediction model to predict the number of infections and material demand. Besides, we established a bi-objective optimization model by constructing a profit and loss matrix and a comprehensive utility perception matrix. The results show that the method is helpful in matching the optimal supply and demand decision quickly on the basis of meeting urgency and satisfaction. The method is helpful in improving the fairness of emergency material distribution, which could better protect people’s livelihoods.
Unless otherwise specified, the chemicals were obtained commercially and used without further purification. Ru-MACHO catalyst was synthesized according to the reported method. 1-4 NMR spectra were recorded on 400 MHz spectrometer with TMS as the internal standard. All coupling constants (J values) were reported in Hertz (Hz). Data are presented as follows: chemical shift in ppm and multiplicity as s = singlet, d = doublet, t = triplet, q = quartet and m = multiplet. Analytical thin layer chromatography (TLC) was performed on precoated silica gel 60 F 254 plates and visualization on TLC was achieved by UV light (254 nm). All chemical shifts are quoted in parts per million (ppm), measured from the center of the signal except in the case of multiplets of more than one proton, which are quoted as a range. Coupling constants are quoted to the nearest 0.1 Hz Coupling constants are quoted to the nearest 0.1 Hz. Melting points (MP) were determined uncorrected. HRMS (ESI) were performed on Fourier Transform Ion Cyclotron Resonance Mass Spectrometer. 2. Typical procedures for the catalytic hydrogenation of -keto esters A glass liner containing a stir bar was charged with substrate (0.5 mmol), base (0.05 mmol), Ru-MACHO (5 umol) and MeOH (0.5 mL) in a glove box. The glass liner was then placed into an autoclave followed by degassing with H 2 three times. The hydrogenation was carried out at 10-50 bar H 2 with stirring at 25 o C or 80 o C for 12-24 h. After the reaction finished, the autoclave was allowed to cool down to r.t. The hydrogen gas was then carefully released in a fume hood, and the solution transferred to a flask with H 2 O (2 ml), extracted with EA (3x5 ml), dried with Na 2 SO 4 and concentrated in vacuo to afford the pure product 2a-2s or 3a-3s. 3 3. Characterization data. 1-phenylethane-1,2-diol(2a): (a known compound), 5 white solid; 62.9 mg; 91%
To meet the national green development trend and realize the sustainable development of human society, the carbon emission in cold-chain distribution is costed. We plan the vehicle distribution path reasonably and optimize the distribution path locally for immediate demand to balance the economic benefits of enterprises and customer satisfaction while reducing the environmental pollution. To minimize distribution cost and maximize customer satisfaction, we design an improved ant colony algorithm to solve the initial distribution path and use the insertion method to solve the immediate customer demand. Taking the actual data of enterprise M as an example, we obtain the optimal distribution path using MATLAB software and optimize the distribution path locally according to the immediate customer demand. The results show that the proposed model and the designed algorithm are practical in satisfying the sustainable development of cold-chain logistics in China.
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