id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
cet-3939	Wang, Y.; Hao, H.X.	Research on the Supply Chain risk Assessment of the Fresh Agricultural Products based on the Improved TOPTSIS Algorithm	2016	6	.pdf	application/pdf	2858	114	53	References Atallah S.S., Gómez M.I., Björkman T., 2014, Localization effects for a fresh vegetable product supply chain: Broccoli in the eastern United States, Food Policy, 49, 151-159, DOI: 10.1016/j.foodpol.2014.07.005 Chen W.C., Li J., Jin X.J., 2016, The replenishment policy of agri-products with stochastic demand in integrated agricultural supply chains, Expert Systems with Applications, 48, 55-66, DOI: 10.1016/j.eswa.2015.11.017 Ge H.T., Gray R., Nolan J., 2015, Agricultural supply chain optimization and complexity: A comparison of analytic vs simulated solutions and policies, International Journal of Production Economics, 159, 208-220, DOI: 10.1016/j.ijpe.2014.09.023 Jacxsens L., Luning P.A., van der Vorst J.G.A.J., Devlieghere F., Leemans R., Uyttendaele M., 2010, Simulation modelling and risk assessment as tools to identify the impact of climate change on 449 microbiological food safety – The case study of fresh produce supply chain, Food Research International, 43, 1925-1935, DOI: 10.1016/j.foodres.2009.07.009 Jayakumar D.N., Venkatesh P., 2014, Glowworm swarm optimization algorithm with topsis for solving multiple objective environmental economic dispatch problem, Applied Soft Computing, 23, 375-386, DOI: 10.1016/j.asoc.2014.06.049 Krohling R.A., Lourenzutti R., Campos M., 2015, Ranking and comparing evolutionary algorithms with Hellinger-TOPSIS, Applied Soft Computing, 37, 217-226, DOI: 10.1016/j.asoc.2015.08.012 Lima F.R. Jr., Osiro L., Carpinetti L.C.R., A comparison between Fuzzy AHP and Fuzzy TOPSIS methods to supplier selection, Applied Soft Computing, 21, 194-209, DOI: 10.1016/j.asoc.2014.03.014 Lourenzutti R., Krohling R.A., 2016, A generalized TOPSIS method for group decision making with heterogeneous information in a dynamic environment, Information Sciences, 330, 1-18, DOI: 10.1016/j.ins.2015.10.005 Mahdevari S., Shahriar K., Esfahanipour A., 2014, Human health and safety risks management in underground coal mines using fuzzy TOPSIS, Science of The Total Environment, 488–489, 85-99, DOI: 10.1016/j.scitotenv.2014.04.076 Mir M.A., Ghazvinei P.T., Sulaiman N.M.N., Basri N.E.A., Saheri S., Mahmood N.Z., Jahan A., Begum R.A., Aghamohammadi N., 2016, Application of TOPSIS and VIKOR improved versions in a multi criteria decision analysis to develop an optimized municipal solid waste management model, Journal of Environmental Management, 166, 109-115, DOI: 10.1016/j.jenvman.2015.09.028 Nong G.P., Pang S.L., 2013, Coordination of Agricultural Products Supply Chain with Stochastic Yield by Price Compensation, IERI Procedia, 5, 118-125, DOI: 10.1016/j.ieri.2013.11.080 Noya I., Aldea X., Gasol C.M., González-García S., Amores M.J., Colón J., Ponsá S., Roman I., Rubio M.A., Casas E., Moreira M.T., Boschmonart-Rives J., 2016, Carbon and water footprint of pork supply chain in Catalonia: From feed to final products, Journal of Environmental Management, 171, 133-143, DOI: 10.1016/j.jenvman.2016.01.039 Othman M.K., Fadzil M.N., Rahman N.S.F.A., 2015, The Malaysian Seafarers Psychological Distraction Assessment Using a TOPSIS Method, International Journal of e-Navigation and Maritime Economy, 3, 40- 50, DOI: 10.1016/j.enavi.2015.12.005 Perdana Y.R., 2012, Logistics Information System for Supply Chain of Agricultural Commodity, Procedia - Social and Behavioral Sciences, 65, 608-613, DOI: 10.1016/j.sbspro.2012.11.172 Vinodh S., Prasanna M., Prakash N.H., 2014, Integrated Fuzzy AHP–TOPSIS for selecting the best plastic recycling method: A case study, Applied Mathematical Modelling, 38, 4662-4672, DOI: 10.1016/j.apm.2014.03.007 Wanke P., Barros C.P., Chen Z.F., 2015, An analysis of Asian airlines efficiency with two-stage TOPSIS and MCMC generalized linear mixed models, International Journal of Production Economics, 169, 110-126, DOI: 10.1016/j.ijpe.2015.07.028 Yu J.F., Wang L., Gong X.L., 2013, Study on the Status Evaluation of Urban Road Intersections Traffic Congestion Base on AHP-TOPSIS Modal, Procedia - Social and Behavioral Sciences, 96, 609-616, DOI: 10.1016/j.sbspro.2013.08.071 450 448 Table 2: Weight of index Second order index Weight Third order index Weight Internal risk 0.32 Risk in choosing suppliers and dealers 0.12 Quality risk of the fresh agricultural products 0.23 Technical risk 0.15 Risk of deterioration for the fresh agricultural products 0.23 Risk management decision 0.17 Quality of supply chain risk 0.05 Structure of the supply chain risk 0.05 External risk 0.25 Credit risks 0.08 Market environment risk 0.11 Demand fluctuation risk 0.26 Supply fluctuation risk 0.26 Natural risk 0.10 Policy risk 0.10 Cooperation risk 0.09 Logistics risk 0.28 Transportation risk 0.33 Distribution of risk 0.33 Inventory risk 0.33 Information risk 0.15 Information transfer risk 0.5 Information security risk 0.5 The distances between each index to the positive and the negative is, 1 0.0786d   , 1 0.1348d   , 2 0.1211d   , 2 0.1105d   3 0.1260d   , 3 0.1088d   , 4 0.0971d   , 4 0.1301d  	cache/cet-3939.pdf	txt/cet-3939.txt