ارائه يك مدل مكان يابي چند دوره اي p- هاب با در نظرگرفتن شبكه ناكامل بين هابي

چكيده انگليسي :

A Multi Period P Hub Location Problem With Incomplete Network Sepehr Jadidi s jadidi@in iut ac ir Date of Submission 2012 05 6 Department of industrial systems engineering Isfahan University of Technology Isfahan 84156 83111 Iran Degree M Sc Language FarsiSupervisor Ali Shahandeh Ali nook @cc iut ac irAbstractIn this thesis we survey a p hub median that the aim is determining of the hub location and allocate non hublocation with hub location so that the transportation cost will be minimum we introduce the DynamicUncapacitated Hub Location Problem DUHLP which consists in minimizing the total cost over a finite timeplanning horizon while ensuring that at each single period all demand is fully routed through the network Thereare two assumptions underlying in this model The first is that all flows have to be consolidated by hubs Thus the paths between O D pairs must include at least one hub node The second is that it is possible to fullyinterconnect hubs with more effective higher volume pathways that allow a discount factor to be applied to thetransportation cost of the flows between any pair of hubs The proposed model has been considered as multi period with discrete demands Periods have been considered as discrete and with constricted Hub location isassumed fixed Also for hub location after end of the period recovery gain is considered The objective functionvalue count as net present worth In this thesis it has been tried to present the model which the hub network to beas incomplete network based on transportation cost so that transportation cost will be minimum Namely there isnot necessarily direct contact between two hub location Because of the difficulty to solve the question and NP hard nature and also in accordance with considered assumes it has been tried to use fewer constraints andvariables Also because to reduce variables we propose a reduction principal The model is formulated as abinary non linear programming In this model we investigate a dynamic time dependent multi commodity wherewe establish new facilities over a given time horizon Despite the difficulty of solving the problem and the nonlinear mathematical model of the third degree in theobjective function showed that solving the model common methods of optimization is not possible in reasonabletime This model is formulated as a mixed binary non linear problem that we propose two solution procedure First procedure is based on branch and bound algorithms and second procedure is based on genetic algorithms Infirst procedure for calculating lower bound we propose a lagrange approach which relaxes some constraints Theresulting model has been divided two subproblem and each subproblem has been solved Briefly the Lagrangefunction exploits the structure of the problem and can be decomposed into smaller subproblems which can besolved efficiently and we use of a sub gradient optimization method to improve the lower bound Then weproposed a heuristic procedure to solve this model with large size Population in genetic algorithm proposed isincluded the original population and the subpopulation The chromosomes is Used in the subpopulation beenconsidered as a matrix A sample of 80 problem generated based on CAB data set and this model was solvedUsing methods presented and results has been studied Results of sample problem compare and the performanceof the proposed genetic algorithm is shown Also according to the results obtained the branch and boundalgorithm proposed is not suitable for large size problemsKeywords Hub location Incomplete network Net present value Branch bound algorithm Genetic algorithms

جديدي، سپهر

ارائه يك مدل مكان يابي چند دوره اي p- هاب با در نظرگرفتن شبكه ناكامل بين هابي

ارزش فعلي , الگوريتم شاخه و كران , الگوريتم ژنتيك