Best Billing & Invoicing Management Software.Best Project Portfolio Management Software.Results of governmental emergency materials transportation are key factors in process of emergency formulating the policy to improve the speed and efficiency for emergency materials transportation during the emergency management process. A typhoon disaster event in Leizhou Peninsula, China, is used as an example to validate the effectiveness and feasibility of the proposed model, as well as to simulate different emergency management strategies. The relationships between influencing factors and the emergency capability were analyzed qualitatively. Using system dynamic model, this paper conducts the simulation study to identify the key influencing factors for the speed of emergency materials transportation. model as they relate to the effective control and guidance of emergency materials transportation. We then explored the internal influence factors and association mechanisms of the dynamic. In the present study, we built a quantitative simulation model underlying the mechanism of emergency materials transportation specifically regarding typhoon disasters. View full-textĮmergency materials transportation, both economic and societal, is one of the most important parts of unconventional emergency management. It can be inferred that the competitive ratio is less than 2.5 and the average flow time for customer orders is less than 30 minutes, which verifies the good performance in both computation efficiency and customer satisfaction of algorithm A. Since it is difficult to get a lower competitive ratio theoretically, the numerical experiments are proposed to analyze the gaps by comparing the values of algorithm A with the ones of offline optimal algorithm A∗ under different situations. The online algorithm A is presented to solve the online problem and is proved to be 21+Qv-competitive, where Qv is the vehicle capacity. Thus, in this paper, we study the online integrated order picking and delivery problem with multizone routing method (IOPDP-MR) to minimize both the maximum delivery completion time and the total delivery cost. It is critical to integrate the order picking and delivery processes and schedule them jointly with a. The online order fulfillment of online-to-offline (O2O) supermarket faces the challenge in how to pick orders from thousands of products on the supermarket shelves and deliver them to customers in different zones and locations by a vehicle routing method within the lowest cost and shortest time. This finding can provide an effective theoretical basis for optimizing the spatial layout of medical isolation areas or the location planning of new medical facilities. In the experiment section, CELRO reduced travel time by at least 14% compared with other methods. Various network sizes and uncertainty combinations are used to design some comparative tests, which aim to verify the effectiveness of the proposed model. To find an appropriate scheme for location of medical isolation areas with the shortest travel times, a co-evolutionary clustering algorithm (CECA), which is a combination of some separated evolutionary programming operations, is proposed to solve the model. Different from previous studies, the vehicle operating characteristics and the interference of uncertainty of the traffic environment are considered in the proposed model. Specifically, this paper solves the following two sub-problems: (i) calculate the shortest transportation times and corresponding routes from any medical isolation area to any person infected or suspected of being infected, and (ii) calculate the location scheme for distribution of isolation areas. To address this problem, this paper proposes a co-evolutionary location-routing optimization (CELRO) model of medical isolation areas for use in major public health emergencies to develop a rapid location-routing scheme for epidemic isolation, including the selection of locations of medical isolation facilities per area and the optimal route per vehicle to each infected person. This has resulted in failure to control the rate of spread of infection cases in time. With the continuous development of the COVID-19 pandemic, the selection of locations for medical isolation areas has not always been optimal for the timely transportation of infected people, or those suspected of being infected.
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