The Study on Multi-base Direct Joint Distribution of Emergency Relief Materials in Large-scale Emergencies
Abstract
After the occurrence of large-scale emergencies, reasonable distribution and efficient delivery of emergency relief supplies determines the success of a rescue operation, which is of vital importance to people’s life and their property safety. Based on the problem of direct distribution of various relief materials to several demand points in the affected areas, by using multiple means of transportation delivering materials from the supply points, considering road condition, numbers, volume and load capacity of carriers, this article sets up a mathematical model which aims at spending the shortest time and using the least number of carriers. This article solves the model by adopting hybrid programming of MATLAB and GAMS. The test proves that this model is correct, the solution speed is fast and the result is reliable.
Full Text:
PDFReferences
Caunhye A. M., Nie X., Pokharel S. (2012). Optimization models in emergency logistics: A literature review. Socio-Economic Planning Sciences, 46(1), 4-13.
Chang F., Wu J., Lee C., Shen H. (2014). Greedy-search-based multi-objective genetic algorithm for emergency logistics scheduling. Expert Systems with Applications, 41(6), 2947-2956.
D’Ambrosio C., Lodi A. (2011). Mixed integer nonlinear programming tools: a practical overview. 4or Quarterly Journal of the Belgian French & Italian Operations Research Societies, 9(9), 329-349.
El-Sherbiny, M. M., Alhamali, R. M. (2013) A hybrid particle swarm algorithm with artificial immune learning for solving the fixed charge transportation problem. Computers & Industrial Engineering, 64(2), 610-620.
Kuang H.S. (2014). Research on Dynamic Vehicle Scheduling Optimization for Urban Joint Distribution under Online Shopping Background. Chongqing University.
Lin Y. H., Batta R., Rogerson P. A., Blatt A., Flanigan M. (2011). A logistics model for emergency supply of critical items in the aftermath of a disaster. Socio-Economic Planning Sciences, 45(4), 132-145.
Manopiniwes W., Irohara T. (2014). A Review of Relief Supply Chain Optimization. Industrial Engineeering and Management Systems, 13(1), 1-14.
Ou Z.W., Wang H.Y., Jiang D.L., LU B.L., GAN W.X., LIANG J. (2004). Emergency logistics. Journal of Chongqing University (Natural Science Edition), 27(3), 164-167.
Özdamar L., Demir O. (2012). A hierarchical clustering and routing procedure for large scale disaster relief logistics planning. Transportation Research Part E Logistics & Transportation Review, 48(3), 591-602.
Yamada T., Taniguchi E., Itoh Y. (2001). Co-operative vehicle routing model with optimal location of logistics terminals. City logistics II, 139-153.
Zhang, Q. (2009). Research on Optimizing Scheme for City Logistics Based on Joint Distribution. China Soft Science.
Zhang X.Y. (2014). Study on Half Open Vehicle Routing Problem in Multi-distribution Center. Dalian Maritime University.
Refbacks
- There are currently no refbacks.

Revista de la Facultad de Ingeniería,
ISSN: 2443-4477; ISSN-L:0798-4065
Edif. del Decanato de la Facultad de Ingeniería,
3º piso, Ciudad Universitaria,
Apartado 50.361, Caracas 1050-A,
Venezuela.
© Universidad Central de Venezuela