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Research On Urgent Relief Quick Response Model And Algorithm For Post-Disaster

Posted on:2016-12-02Degree:DoctorType:Dissertation
Country:ChinaCandidate:G ChenFull Text:PDF
GTID:1226330485483279Subject:Logistics Engineering
Abstract/Summary:PDF Full Text Request
Natural disaters in china have some unique characteristics, sunch as variety, widespread, high frequency, serious losses, etc. In the presence of increasingly frequent natural disasters, we need to establish a efficient, reliable and stable urgent relief quick response system to minimize the loss caused by disasters. From the practice of dister relief operation in recent years, there are three key problems need to be solved immediately. First, how to distribute relief commodities. We need to consider the geograghical distribution and traffic condition of the supply spots, distribution centers and affected areas, and make a decision of types and quantities of relief commodities. Second, how to locate the temporary facilities. We need to consider the geographical distribution and allocated relationship of the affected spots, and make a decision of the number and location of the facilities, for purpose of reducing the operation cost of distribution centers and distribution cost of the vehicles. Third, how to optimize the distribution route, "the last kilometer" of relief commodities distribution is particularly important, we need to consider the geograghical distribution of the affected areas, the road condition and the number and capacity of the vehicle. The above problems are not independent and influence each other, it is necessary to carry out the combination optimization for the three problems. Hence, we carry out our research as follows.Firstly, considering the urgent relief needs right after disaster, developed a three-layer urgent relief quick response system that including relief warehouse, relief distribution center, and affected areas, presented a combination optimization model with the goal of shortest operation time to deciding relief scheduling and vehicle routing. According to the characteristics of the model, proposed a improved ant colony algorithm based on the saving method and the minimum cost maximum flow approach, the results of an example show feasibility and efficacy of the proposed model and algorithm.Then, a combination optimization model is proposed with the goals of minimizing the unsatisfied demands, total time and total cost, based on the periodic characteristics of urgent relief operations, such as multi-comodity, multi-period, multimodal and etc. Temporary emergency facility location and urgent relief allocation have been considered in this model. The multi-objective formulation is solved by lexicographic method. Considering the uncertainty of the demand and supply information, a modified fuzzy multi-objective decision optimization model was proposed besed on the above model, an epsilon-constraint method was employed to solve the multi-objective model. A numerical study shows that the model and solving method could provide logistics solutions for decision-makers under different preferences.At last, a bi-level optimization model was proposed considering the uncertain demand. The location of distribution centers and the route scheduling of delivery vehicles are decided by the upper model with the goals of minimizing the last arrival time, minimizing the total delivery cost and maximizing the vehicle load utilization. The location of transshipment depots and the allocation of relief commodities are decided by the lower model with the goal of minimizing the total transportation cost. A self-adaptive genetic algorithm was proposed to solve the model, roulette, variable crossover and cariation probability were employed in case of premature convergence of the algorithm. A numerical example was presented to verify the feasibility and effectiveness of the model and algorithm. In addition, a heuristic algorithm based on the Non-dominated Sorting Genetic Algorithm II (NSGAII) was proposed. The results of a numerical example show that The quality of the Pareto optimal solutions obtained by the heuristic algorithm is quite well and the heuristic algorithm have a good performance in the convergence, robustness and computational efficiency.This paper studied the combination optimization problem of urgent relief commodities allocation, emergency facility location, and vehicle routing, which provided a new research ideas and methods for the emergency logistics system optimization theory. In the end, we indicate that the emergency resource allocation problem of considering fairness, emergency rescue problem of considering victims psychological behavior and emergency resource allocation between different affected areas of considering multiple delivery modes are worthy of further study.
Keywords/Search Tags:emergency logistics, combination optimization problem, quick response, multi-objective optimization, improved ant colony algorithm, adaptive genetic algorithm, Non-dominated Sorting Genetic Algorithm Ⅱ
PDF Full Text Request
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