VEHICLE ROUTING PROBLEM WITH MULTIPLE TRIP, TIME WINDOWS, MULTIPLE DEPOT AND SIMULTANEOUS PICKUP-DELIVERY

One of the cost component in total logistic cost is transportation cost. To acquire optimum transportation cost, proper transportation planning toward routes determination and vehicle scheduling commonly called as Vehicle Routing Problem (VRP). This research has developed mathematical model and prob...

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Bibliographic Details
Main Author: FRIADI (NIM : 23415013), AGUS
Format: Theses
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/20818
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:One of the cost component in total logistic cost is transportation cost. To acquire optimum transportation cost, proper transportation planning toward routes determination and vehicle scheduling commonly called as Vehicle Routing Problem (VRP). This research has developed mathematical model and problem solving algorithm in VRP cases which consider multiple trip, time windows, and simultaneous pickup-delivery at multiple depot. (VRP-MTTWSPDMD) <br /> <br /> Objective function of mathematical formulation in this research is to minimize trip cost during planning horizon by minimizing amount of vehicle used and total tour duration time. On problem solving algorithm, generation of initial route solution conducted with heuristic method Sequential Insertion. This initial route solution then regenerated to acquire better solution using Particle Swarm Optimization algorithm. Both Sequential Insertion and Particle Swarm Optimization algorithm are used to find solution from each depot by clustering the closest costumer from the depot. The result then improved again by Simulated Annealing algorithm using improvement process by utilizing operator relocation and swap. <br /> <br /> Algorithm developed from this research give result faster average computing time which has gap -99,0401 % compared with analytic calculation of optimum solution. Meanwhile if looked from value of objective function, calculation using algorithm approached optimum solution result analytically with gap 0,000213 %.