scholarly journals Penyelesaian Vehicle Routing Problem Untuk Efisiensi Rute Pendistribusian Produk Minuman Teh Pucuk Harum Menggunakan metode Saving Matriks Studi Kasus (PT. Cipta Niaga Semesta Palu)

2020 ◽  
Vol 17 (1) ◽  
pp. 17-28
Author(s):  
R Putrafi ◽  
A Sahari
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Product Distribution ◽  
Routing Problem ◽  
Distribution Costs ◽  
Efficient Delivery ◽  
Distribution Process ◽  
Total Difference ◽  
The Cost ◽  
A Company

Vehicle Routing Problem Is a Problem related to the route of product distribution to the consumers. With the existence of these problems a company is expected to seek away a way so that the distribution process can arrive on time to scattered consumers and obtain more efficient routes and costs. Therefore a method which can help the process of scheduling a good route and obtaining optimum costs and efficient delivery was used. One of the methods used was Saving Matrix, which in its operation could efficient the delivery route so that the minimum total distance was obtained. The company's actual mileage was greater than the distance travelled by the route after using the Saving Matrix method. The total difference in distance produced was 106,35 km or more saving 41,2 % from the actual distance of the company and using Saving Matrix could save the distribution costs of Rp. 5.687.640 or save 33,8 % of the cost before applying the method.

scholarly journals Distribusi Batik Madura Melalui Penerapan Generalized Vehicle Routing Problem (GVRP)

2017 ◽  
Vol 3 (2) ◽  
pp. 101-104
Author(s):  
Faisol Faisol ◽  
Masdukil Makruf
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Product Distribution ◽  
Cluster Method ◽  
Routing Problem ◽  
Maximum Capacity ◽  
Distribution Process ◽  
The Cost ◽  
Distribution Cost ◽  
Generalized Vehicle Routing Problem

Product distribution process is an effort to convey a product of consumer handlebar with a planned and programmed system. Cluster method is a grouping of the nearest market location, then analyzed the location of potential facilities through center of gravity. GVRP (Generalized Vehicle Routing Problem) is one of the algorithms in the cluster method [1]. In the GVRP describes the route determination to minimize the required distribution costs. GVRP is a generalization of VRP, so the point of the graph is partitioned into several sets of specific points, called clusters [2]. In this research, modification of GVRP model for multi-capacity vehicle case can determine the route and minimize the cost of distribution. Taken case on UD. Damai Asih for the distribution of Madura writes batik to 25 districts in East Java. From the results of running using MATLAB 7.8.0 obtained the efficiency of the distribution cost of 8.71% of the initial cost before doing the clustering based on distance and maximum capacity of the car of Rp. 6,969,480.00. After the filtering based on the distance and maximum capacity of the car obtained a cost of Rp. 6.365.500.00. The highest value of efficiency is obtained in cluster four, while the lowest efficiency value is obtained in cluster eight. The existence of cost efficiency is due to the different mileage in the clustering process.

scholarly journals Brief communication: Vehicle routing problem and UAV application in the post-earthquake scenario

2017 ◽  
Author(s):  
Marco Cannioto ◽  
Antonino D'Alessandro ◽  
Giosuè Lo Bosco ◽  
Salvatore Scudero ◽  
Giovanni Vitale
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Seismic Event ◽  
Computing Time ◽  
Research Problem ◽  
Routing Problem ◽  
Earthquake Scenario ◽  
Short Computing Time ◽  
The Cost ◽  
The Town

Abstract. In this paper we simulate a Unmanned Aerial Vehicle's (UAV) recognition after a possible case of diffuse damage after a seismic event in the town of Acireale (Sicily, Italy). Given a set of sites (84 relevant buildings) and the range of the UAV, we are able to find the number of vehicles to employ and the shortest survey path. The problem of finding the shortest survey path is an operational research problem called Vehicle Routing Problem (VRP) whose solution is known to be computationally time-consuming. We used the Simulated Annealing (SA) heuristic that is able to provide stable solutions in relatively short computing time. We also examined the distribution of the cost of the solutions varying the depot on a regular grid in order to assess the best area where to execute the survey.

The Research on VRP Based on Max-Min Ant Colony Algorithm

2011 ◽  
Vol 219-220 ◽  
pp. 1285-1288 ◽  
Author(s):  
Chang Min Chen ◽  
Wei Cheng Xie ◽  
Song Song Fan
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Ant Colony Algorithm ◽  
Search Time ◽  
Ant Colony ◽  
Local Optimum ◽  
Simulation Data ◽  
Routing Problem ◽  
Np Hard Problem ◽  
The Cost

Vehicle routing problem (VRP) is the key to reducing the cost of logistics, and also an NP-hard problem. Ant colony algorithm is a very effective method to solve the VRP, but it is easy to fall into local optimum and has a long search time. In order to overcome its shortcomings, max-min ant colony algorithm is adopted in this paper, and its simulation system is designed in GUI of MATLAB7.0. The results show that the vehicle routing problem can well achieves the optimization of VRP by accessing the simulation data of database.

Practical aspects of the split delivery vehicle routing problem (SDVRP)

2018 ◽  
Vol 120 ◽  
pp. 155-166
Author(s):  
Marek Karkula
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Route Planning ◽  
Product Distribution ◽  
Delivery Vehicle ◽  
Routing Problem ◽  
Split Delivery ◽  
Delivery Planning ◽  
Distribution Company ◽  
Planning Problems

Transport process arrangement and delivery route planning is one of the most important tasks of managers in distribution, trade and production enterprises. The problem of route planning concerns the rationalization of product distribution processes offered by company for the customer's network. In operational research, such a problem is included in the class of issues of Vehicle Routing Problem – VRP. The VRP delivery planning problems constitute a wide family of issues arising primarily from the conditions and constraints of the practice. The paper presents the practical application of one of the VRP variants – the problem of arranging routes for the Split Delivery Vehicle Routing Problem – SDVRP, and the results of analyses based on research carried out in a distribution company.

scholarly journals Solving Close-Open Mixed Vehicle Routing Problem Using Bat Algorithm

2020 ◽  
Vol 2 (1) ◽  
pp. 46
Author(s):  
Atika Dwi Hanun Amalia ◽  
Herry Suprajitno ◽  
Asri Bekti Pratiwi
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Large Data ◽  
Bat Algorithm ◽  
Small Data ◽  
Routing Problem ◽  
Java Programming ◽  
Implementation Program ◽  
Distribution Process ◽  
Vehicle Capacity

The purpose of this research is to solve the Close-Open Mixed Vehicle Routing Problem (COMVRP) using Bat Algorithm. COMVRP which is a combination of Close Vehicle Routing Problem or commonly known as Vehicle Routing Problem (VRP) with Open Vehicle Routing Problem (OVRP) is a problem to determine vehicles route in order to minimize total distance to serve customers without exceed vehicle capacity. COMVRP occurs when the company already has private vehicles but its capacity could not fulfill all customer demands so the company must rent several vehicles from other companies to complete the distribution process. In this case, the private vehicle returns to the depot after serving the last customer while the rental vehicle does not need to return. Bat algorithm is an algorithm inspired by the process of finding prey from small bats using echolocation. The implementation program to solve was created using Java programming with NetBeans IDE 8.2 software which was implemented using 3 cases, small data with 18 customers, medium data with 75 customers and large data with 100 customers. Based on the implementation results, it can be concluded that the more iterations, the smaller total costs are obtained, while for the pulse rate and the amount of bat tends not to affect the total cost obtained.

scholarly journals The Joint Network Vehicle Routing Game

2020 ◽  
Author(s):  
Mathijs van Zon ◽  
Remy Spliet ◽  
Wilco van den Heuvel
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Cost Allocation ◽  
Allocation Problem ◽  
Routing Problem ◽  
Generation Algorithm ◽  
Core Allocation ◽  
New Variant ◽  
Delivery Routes ◽  
The Cost

Collaborative transportation can significantly reduce transportation costs as well as greenhouse gas emissions. However, allocating the cost to the collaborating companies remains difficult. We consider the cost-allocation problem, which arises when companies, each with multiple delivery locations, collaborate by consolidating demand and combining delivery routes. We model the corresponding cost-allocation problem as a cooperative game: the joint network vehicle routing game (JNVRG). We propose a row generation algorithm to either determine a core allocation for the JNVRG or show that no such allocation exists. In this approach, we encounter a row generation subproblem, which we model as a new variant of a vehicle routing problem with profits. Moreover, we propose two main acceleration strategies for the row generation algorithm. First, we generate rows by relaxing the row generation subproblem, exploiting the tight linear programming (LP) bounds for our formulation of the row generation subproblem. Secondly, we propose to also solve the row generation subproblem heuristically and to only solve it to optimality when the heuristic fails. We demonstrate the effectiveness of the proposed row generation algorithm and the acceleration strategies by means of numerical experiments for both the JNVRG as well as the traditional vehicle routing game, which is a special case of the JNVRG. We create instances based on benchmark instances of the capacitated vehicle routing problem from the literature. We are able to either determine a core allocation or show that no core allocation exists, for instances ranging from 5 companies with a total of 79 delivery locations to 53 companies with a total of 53 delivery locations.

scholarly journals Analysis of an Automated Vehicle Routing Problem in Logistics considering Path Interruption

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Yong Zhang ◽  
Lei Shi ◽  
Jing Chen ◽  
Xuefeng Li
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Initial Period ◽  
Pso Algorithm ◽  
Automated Vehicles ◽  
Routing Problem ◽  
Automated Vehicle ◽  
Last Mile ◽  
The Cost

The application of automated vehicles in logistics can efficiently reduce the cost of logistics and reduce the potential risks in the last mile. Considering the path restriction in the initial stage of the application of automated vehicles in logistics, the conventional model for a vehicle routing problem (VRP) is modified. Thus, the automated vehicle routing problem with time windows (AVRPTW) model considering path interruption is established. Additionally, an improved particle swarm optimisation (PSO) algorithm is designed to solve this problem. Finally, a case study is undertaken to test the validity of the model and the algorithm. Four automated vehicles are designated to execute all delivery tasks required by 25 stores. Capacities of all of the automated vehicles are almost fully utilised. It is of considerable significance for the promotion of automated vehicles in last-mile situations to develop such research into real problems arising in the initial period.

scholarly journals A New Hybrid Butterfly Optimization Algorithm for Green Vehicle Routing Problem

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Dana Marsetiya Utama ◽  
Dian Setiya Widodo ◽  
Muhammad Faisal Ibrahim ◽  
Shanty Kusuma Dewi
Keyword(s):  
Vehicle Routing ◽  
Optimization Algorithm ◽  
Vehicle Routing Problem ◽  
Computation Time ◽  
Industrial Sector ◽  
Routing Problem ◽  
Distribution Costs ◽  
Critical Problems ◽  
Distribution Cost ◽  
Fuel Costs

In the industrial sector, transportation plays an essential role in distribution. This activity impacts climate change and global warming. One of the critical problems in distribution is the green vehicle routing problem (G-VRP). This study focuses on G-VRP for a single distribution center. The objective function is to minimize the distribution costs by considering fuel costs, carbon costs, and vehicle use costs. This research aims to develop the hybrid butterfly optimization algorithm (HBOA) to minimize the distribution costs on G-VRP. It was inspired by the butterfly optimization algorithm (BOA), which was by combining the tabu search (TS) algorithm and local search swap and flip strategies. BOA is a new metaheuristic algorithm that has been successfully applied in various engineering fields. Experiments were carried out to test the parameters of the proposed algorithm and vary the speed of vehicles. The proposed algorithm was also compared with several procedures of prior study. The experimental results proved that the HBOA could minimize the total distribution cost compared to other algorithms. Moreover, the computation time is also included in the analysis.

scholarly journals CAPACITATED VEHICLE ROUTING PROBLEM

2019 ◽  
Vol 7 (3) ◽  
pp. 310-327
Author(s):  
Ibrahim A.A ◽  
Lo N. ◽  
Abdulaziz R.O ◽  
Ishaya J.A
Keyword(s):  
Reinforcement Learning ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Routing Problem ◽  
Goods And Services ◽  
Capacitated Vehicle Routing Problem ◽  
Large Size ◽  
The Cost ◽  
Cost Of Transportation ◽  
Capacitated Vehicle

Cost of transportation of goods and services is an interesting topic in today’s society. The  Capacitated vehicle routing problem, which is been consider in this research, is one of the variants of the vehicle routing problem. In this research we develop a reinforcement learning technique to find optimal paths from a depot to the set of customers while also considering the capacity of the vehicles, in order to reduce the cost of transportation of goods and services. Our basic assumptions are; each vehicle originates from a depot, service the customers and return to the depot, the vehicles are homogeneous. We solve the CVRP with an exact method; column generation, goole’s operation research tool and reinforcement learning and compare their solutions. Our objective is to solve a large-size of vehicle routing problem to optimality.

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