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Due to the uncertainty and information delay of disaster situations, emergency relief material distribution and vehicle scheduling often face complex environments where demand point information dynamically changes during the distribution process. It is particularly important to quickly respond and accurately and efficiently achieve emergency material rescheduling in a dynamically changing environment. A dynamic emergency logistics model was established for emergency supplies in a complex environment with dynamic changes in demand point information, and a dynamic optimization algorithm was proposed based on cluster-distribution strategy. Corresponding route adjustment strategies were designed to ensure the feasibility of the plan. Finally, genetic algorithm was used to solve the problem. The numerical experimental results demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Shenzhen University Science & Engineering is the property of Editorial Department of Journal of Shenzhen University Science & Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Railway Science & Engineering is the property of Journal of Railway Science & Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to improve the efficiency of emergency supplies distribution during an earthquake, reduce casualties and economic losses, road damage is considered as an important factor affecting the distribution of emergency supplies. According to the characteristics of earthquake emergency material distribution, considering the time window constraints of emergency material distribution, a dual-objective model of total time function and total cost function is established. Combining the characteristics of the model, a hybrid algorithm combining genetic algorithm and simulated annealing algorithm is designed. The result of calculation example shows that the algorithm has a faster convergence rate. Further compare with not considering road damage, the result shows that the total delivery time, total cost, and penalty cost are reduced when the road damage is taken into account, which further validates the model the superiority. It is concluded that the model and algorithm can effectively solve the problem of optimizing the distribution route of emergency supplies considering road damage, improve the efficiency of emergency logistics, and reduce the loss caused by the earthquake. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Railway Science & Engineering is the property of Journal of Railway Science & Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Food Science & Technology & Economy is the property of Grain Science & Technology & Economy Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper proposed a two-stage emergency logistics transportation and redistribution strategy for the problems con- sidering the transportation timeliness and the supplies distribution fairness in emergency logistics. Firstly, This paper proposed the capacitated vehicle routing problem with maximum time satisfaction( CVRP-MTS) for emergency vehicle transport schedu- ling and the emergency supplies distribution problem with minimum weighted standard deviation of satisfactions ( EMDP-MWS- DS) based on the time satisfaction, the supplies satisfaction and the comprehensive satisfaction defined in this paper. Then this paper designed a hybrid grey wolf optimization algorithm( HGWOA) to solve the CVRP-MTS in the first stage. The HGWOA adopted the optimal split procedure decoding strategy, and adopted the chaotic search strategy, the 2-0pt and 1-1 local search strategy to improve the search ability of the algorithm. And this paper implemented the chaotic grey wolf optimization algorithm ( CGWOA) to solve the EMDP-MWSDS in the second stage. The experimental results show that in the first stage, overall time satisfaction of the CVRP-MTS is 39. 31 % higher than that of the CVRP model. In the second stage, when 80% of the actual material quantity and 0. 75 for the weight coefficient, the standard deviation of the comprehensive satisfaction degree is 0. 061 9, and the standard deviation of the supplies satisfaction degree is 0. 097 4. The distribution results effectively balance the victims' psychological demands and supplies utilization efficiency. The two-stage emergency logistics transportation and supplies redistribution distribution strategy can obtain high time satisfaction and good supplies distribution results, which prove the effectiveness of the proposed models and algorithms. [ABSTRACT FROM AUTHOR]

For the multi-objective vehicle routing problem in emergency logistics distribution, this paper proposed an improved intelligent water drops algorithm for multi-objective routing programming scheduling of emergency materials. 'Hie main contents consist of four steps: a)constructed the disease spreading model in multiple areas based on Holling- K function, b)data fusion to forecast the relief demand in multiple areas, c) built the multi-objective mathematical model with the minimum emergency logistics distribution time and cost, d) designed an improved intelligent wrater drops algorithm for multi-objective emergency materials distribution path optimization. 'Hie results show that the established model and algorithm are effective and feasible, which can provide references for decision makers of emergency logistics management. [ABSTRACT FROM AUTHOR]

The emergence resources are limited and the demands are uncertain in the critical period of the disaster. In order to improve the efficiency of the emergence logistics, the allocation of the emergence resources and the vehicle routing should be determined simultaneously. Based on the assumption of the stochastic demands were normal distributions, it developed the optimal model of the emergence vehicle routing considering the stochastic demand, which objective function was to minimize the transportation costs and the costs caused by the supplies more or less than the actual demands, under the conditions of the time windows and load capacity. According to the characteristic of the model, this paper proposed the genetic algorithm to solve the model. The application shows that the method operates quickly and the results are rational, which can provide scientific basis for decision-making. [ABSTRACT FROM AUTHOR]

This paper studies the type-2 fuzzy pre-positioning problem for emergency supplies on the basis of fuzzy possibility theory. Because of the uncertainty about the transportation costs, the suppliers5 supply amounts, the affected areas5 demands and the capacities of the roads, we characterize these parameters by type-2 fuzzy variables and build a pre-positioning model of emergency supplies with expected value criterion under type-2 fuzzy environment. According to the value-at-risk (VaR) reduction method, we deduce the expectation value formula for the reduced fuzzy variables of type-2 triangular fuzzy variable. When the type-2 fuzzy variables are independent and triangular distributions, we can convert the original model into its equivalent model, which is a mixed-integer parametric programming model and can be solved by Lingo. Finally, we present an example to illustrate the modeling idea presented in our paper. The computational results verify the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

In post-disaster relief operations, the panic psychology of victims may influence the whole relief operation. This paper considered the effects of psychological costs of victims when waited for evacuation from disaster sites and waited for relief resources in shelters to the relief operation, developed a mixed-integer linear programming model to select resource supply depots and produced plans for victim evacuation and resource distribution in the short-term following a disaster in a way that minimizes the economic cost of logistical operations and the psychological cost to victims. Experimental studies verify the proposed model, results show that the society should give full consideration to the victims panic psychology in the relief operation. [ABSTRACT FROM AUTHOR]

Aim at the problem for how to analyze the propensity to spread of shortage of supplies in emergency logistics decision support system, this paper proposed a new model to study the propensity to spread of shortage of supplies for emergency logistics network. This paper, by the mechanism of viral spreading and introducing the parameter of time "t", it constructed SI-SIRS ( susceptible infective and susceptible infective recover susceptible) model to analyze the scale-free network which included 61 nodes. Case analysis shows that SIRS effectively depicts the spread behavior of shortage of supplies in emergency logistics network. Propensities to spread of shortage of supplies are effected by node self-spread ability, network topology, individual nodes differences and responding mechanism of emergency logistics. [ABSTRACT FROM AUTHOR]

This paper addressed a multi-supplier multi-affected area multi-relief and multi-vehicle emergency vehicles location, path selection and relief allocation problem. Considering the inherent trade-off between disaster forecast accuracy and logistics cost efficiency, a multi-objective stochastic programming model was proposed. The features were: the demand and availability of relief-allocation path were stochastic, and there were coverage limits for relief suppliers to cover affected areas. The multi-objective programming model was transformed into a single-objective programming model by the use of a weighted Bayes risk; and the proposed model was transformed into an optimal stopping problem by designing a decision rule. The model was solved by using Xpress. Numerical results indicate the velocity and accuracy of the model and software, and demonstrate the superiority of two-stage stochastic programming and disaster scenario information updates respectively. [ABSTRACT FROM AUTHOR]

Since demand of emergency materials is usually uncertain and continuous and the emergency rescue proceeding which is consist of more than one period always takes place in multiple epidemic areas at the same time, an optimal multi-period collaborative scheduling of emergency materials for multiple epidemic areas is proposed. Firstly, with the consideration of the delay caused by the latent period of an epidemic and the collaborative strategy based on vertical distribution and transverse transportation, a multi-objective stochastic programming model for an emergency logistics network is constructed based on the epidemic diffusion rules. Then the genetic algorithm is adopted to solve the optimization model. Finally, the application of the model is given by a numerical example. [ABSTRACT FROM AUTHOR]