VEHICLE ROUTING PROBLEM, SEQUENTIAL INSERTION, GENETIC ALGORITHM, MULTIPLE TRIPS, SPLIT DELIVERY, MULTIPLE PRODUCTS, MULTIPLE COMPARTMENTS, TIME WINDOWS

Distribution system planning is needed to improve efficiency in the company's operational activities. This can be achieved by determining the number of fleet usage and the exact route, commonly called as Vehicle Routing Problem (VRP). This research has developed mathematical model and problem s...

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Main Author: MUTHIA NIM : 23415016, METHA
Format: Theses
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/28869
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:28869
spelling id-itb.:288692018-03-16T09:08:31Z VEHICLE ROUTING PROBLEM, SEQUENTIAL INSERTION, GENETIC ALGORITHM, MULTIPLE TRIPS, SPLIT DELIVERY, MULTIPLE PRODUCTS, MULTIPLE COMPARTMENTS, TIME WINDOWS MUTHIA NIM : 23415016, METHA Indonesia Theses INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/28869 Distribution system planning is needed to improve efficiency in the company's operational activities. This can be achieved by determining the number of fleet usage and the exact route, commonly called as Vehicle Routing Problem (VRP). This research has developed mathematical model and problem solving algorithm in VRP with multiple trips, split delivery, multiple products, multiple compartments, and time windows (VRP-MTSDMPCTW). The model in this research is used in the distribution of fuel PT. Pertamina in NTT and Timor Leste. <br /> <br /> <br /> <br /> Objective function of mathematical formulation in this research is to minimize trip cost during planning horizon by minimizing the number of vehicles and total travel time to serve all customer requests. The model in this research solved by using two stages of the solution construction. The first stage is to use the algorithm called Sequential Insertion (SI) to obtain an initial feasible solution. The second stage is to improve the initial solution with Genetic Algorithm (GA) to obtain the best solution using mutation and crossover operators. <br /> <br /> <br /> <br /> The developed algorithm is able to produce solution 81,72% faster than the analytical calculation. For the objective function, the developed algorithm is able to produce a solution approaching the optimal solution with gap 1.14%. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description Distribution system planning is needed to improve efficiency in the company's operational activities. This can be achieved by determining the number of fleet usage and the exact route, commonly called as Vehicle Routing Problem (VRP). This research has developed mathematical model and problem solving algorithm in VRP with multiple trips, split delivery, multiple products, multiple compartments, and time windows (VRP-MTSDMPCTW). The model in this research is used in the distribution of fuel PT. Pertamina in NTT and Timor Leste. <br /> <br /> <br /> <br /> Objective function of mathematical formulation in this research is to minimize trip cost during planning horizon by minimizing the number of vehicles and total travel time to serve all customer requests. The model in this research solved by using two stages of the solution construction. The first stage is to use the algorithm called Sequential Insertion (SI) to obtain an initial feasible solution. The second stage is to improve the initial solution with Genetic Algorithm (GA) to obtain the best solution using mutation and crossover operators. <br /> <br /> <br /> <br /> The developed algorithm is able to produce solution 81,72% faster than the analytical calculation. For the objective function, the developed algorithm is able to produce a solution approaching the optimal solution with gap 1.14%.
format Theses
author MUTHIA NIM : 23415016, METHA
spellingShingle MUTHIA NIM : 23415016, METHA
VEHICLE ROUTING PROBLEM, SEQUENTIAL INSERTION, GENETIC ALGORITHM, MULTIPLE TRIPS, SPLIT DELIVERY, MULTIPLE PRODUCTS, MULTIPLE COMPARTMENTS, TIME WINDOWS
author_facet MUTHIA NIM : 23415016, METHA
author_sort MUTHIA NIM : 23415016, METHA
title VEHICLE ROUTING PROBLEM, SEQUENTIAL INSERTION, GENETIC ALGORITHM, MULTIPLE TRIPS, SPLIT DELIVERY, MULTIPLE PRODUCTS, MULTIPLE COMPARTMENTS, TIME WINDOWS
title_short VEHICLE ROUTING PROBLEM, SEQUENTIAL INSERTION, GENETIC ALGORITHM, MULTIPLE TRIPS, SPLIT DELIVERY, MULTIPLE PRODUCTS, MULTIPLE COMPARTMENTS, TIME WINDOWS
title_full VEHICLE ROUTING PROBLEM, SEQUENTIAL INSERTION, GENETIC ALGORITHM, MULTIPLE TRIPS, SPLIT DELIVERY, MULTIPLE PRODUCTS, MULTIPLE COMPARTMENTS, TIME WINDOWS
title_fullStr VEHICLE ROUTING PROBLEM, SEQUENTIAL INSERTION, GENETIC ALGORITHM, MULTIPLE TRIPS, SPLIT DELIVERY, MULTIPLE PRODUCTS, MULTIPLE COMPARTMENTS, TIME WINDOWS
title_full_unstemmed VEHICLE ROUTING PROBLEM, SEQUENTIAL INSERTION, GENETIC ALGORITHM, MULTIPLE TRIPS, SPLIT DELIVERY, MULTIPLE PRODUCTS, MULTIPLE COMPARTMENTS, TIME WINDOWS
title_sort vehicle routing problem, sequential insertion, genetic algorithm, multiple trips, split delivery, multiple products, multiple compartments, time windows
url https://digilib.itb.ac.id/gdl/view/28869
_version_ 1821995201061715968