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Dissertation Research On The Optimization Issue Of Army's Material Transportation Routes For A Certain Area Based Ant Colony Algorithm

Posted on:2017-12-04Degree:MasterType:Thesis
Country:ChinaCandidate:H M WangFull Text:PDF
GTID:2416330569998780Subject:Project management
Abstract/Summary:PDF Full Text Request
Just like the saying: an army marches on its stomach,logistical support plays an important role in the victory of a war from the ancient times.Military logistics whose important role has been confirmed by the history is a key component of logistics.With the development of science and technology,the world's military technologies have undergone enormous changes,which also led to the modern reform trend of military logistics support.The demands of logistics support in modern war do not decrease within the modernization of technology and information,but make a significant increase in the status of logistics support.At present,the modernization of our army is facing a critical period of strategic opportunity,and the reform of military logistics will have an extensive and far-reaching influence on the modernization of our army.However,the objective of modernization reform of military logistics is: how to use efficient,fast and accurate ways of transportation and information technology means to complete the transportation and supply of military supplies,and to meet the requirements of army's logistics for various tasks,which has become a new research field of military logistics management and military logistics.Therefore,the research on the military material transportation routes and vehicle scheduling can improve the capacities of logistics support and the resource utilization of our army to a certain extent.The research of this paper,in line with the overall demands of current army logistics support tasks and the appropriate situation in the army,which has an important practical significance.Based on the introduction of research backgrounds,current research situation at home and abroad and the summary of related theories and knowledge on the logistics transportation and military logistics,the paper mainly researches three contents as below:(1)First,we establish the improved ant colony algorithm model for the path selection of logistics materials transportation in a regional armies.We mainly define the probability distributions of the state transfer,set up some strategies for updating local information,while optimize the strategies for the global updating of ant searches.Based on this,the path optimization model of logistic materials transportation named Vehicle Routing Problem with Time Windows constraints(VRPTW)which is feasible to the regional forces is proposed.(2)Secondly,according to the actual situation of regional army's materials transportation and distribution,the initial data acquisitions and settings of VRPTW and its algorithms are done,and the optimization and improvement steps of the algorithm and VRPTW model's assumptions are expounded.On this basis,taking the actual route planning in this regional army's transport as an example,using the Matlab programs to simulate the established algorithm in VRPTW model,finally the optimal transport strategies are got.(3)Finally,in order to scientifically,efficiently and intelligently accomplish the tasks of military materials transportation,the paper uses the project management software named Project 2010 to carry out the schedules plan,processes control,resources allocation of the military logistics transportation plans in regional armies.This research has a good supporting impact for the selection and optimization of logistics transportation path in the regional armies,which can effectively reduce the cost,save the transportation time,save the transportation resources in the regional logistic material transportation;at the same time,it can provide some excellent references for other similar armies in the choice of logistics transportation routes.
Keywords/Search Tags:Military materials transportation, Transportation path optimization, VRP model, Improved ant colony algorithm, Project management
PDF Full Text Request
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