scholarly journals Route Selection and Distribution Cost of Express Delivery: An Urban Metro Network Based Study

2021 ◽  
Vol 33 (2) ◽  
pp. 283-296
Author(s):  
Junhua Guo ◽  
Yutao Ye ◽  
Yafeng Ma
Keyword(s):  
Programming Model ◽  
Case Analysis ◽  
Delivery Mode ◽  
Route Selection ◽  
Distribution Costs ◽  
Time Periods ◽  
Distribution Cost ◽  
Standard Genetic Algorithm ◽  
Metro Network ◽  
Express Delivery

Route selection and distribution costs of express delivery based on the urban metro network, referred to as metro express delivery (MeD), is addressed in this study. Considering the characteristics of express delivery transportation and the complexity of the urban metro network, three distribution modes of different time periods are proposed and a strict integrated integer linear programming model is developed to minimize total distribution costs. To effectively solve the optimal problem, a standard genetic algorithm was improved and designed. Finally, the Ningbo subway network is used as an example to confirm the practicability and effectiveness of the model and algorithm. The results show that when the distribution number of express delivery packages is 1980, the three different MeD modes can reduce transportation costs by 40.5%, 62.0%, and 59.0%, respectively. The results of the case analysis will help guide express companies to collaborate with the urban metro network and choose the corresponding delivery mode according to the number of express deliveries required.

An urban metro network-based method to evaluate carbon emission and distribution cost of express delivery

2021 ◽  
pp. 1-14
Author(s):  
Junhua Guo ◽  
Xiaofang Xiao ◽  
Yutao Ye ◽  
Lixin Yan
Keyword(s):  
Carbon Emissions ◽  
Programming Model ◽  
Transportation Cost ◽  
Transportation Costs ◽  
Delivery Method ◽  
Nsga Ii ◽  
Coding Method ◽  
Distribution Cost ◽  
Metro Network ◽  
Express Delivery

A novel green delivery method for express delivery based on the urban metro network, referred to as Green metro express delivery (GMED), is presented. A multi-objective mathematical programming model is first proposed to maximize the search for the best transportation costs and lowest carbon emissions. To solve the GMED model e-ciently, a two-layer coding method is used to encode the path and the non-dominated sorting genetic algorithm II (NSGA-II) is adopted. Finally, a numerical experiment was conducted with Ningbo Metro Network as a case to prove the effectiveness and stability of NSGA-II in solving the GMED model. The result shows that: (a) Compared with the vehicle express delivery method (VED), GMED has lower carbon emissions and vehicle mileage. (b) For the same quantity of express delivery, the transportation costs of GMED and VED have their own advantages over different transportation distances. (c) For delivery distances with the same transportation cost, the lager the quantity of express delivery, the lower the transportation cost of GMED compared to VED.

scholarly journals OPTIMALISASI PENDISTRIBUSIAN BARANG DI PT.SINAR NIAGA SEJAHTERA PALU MENGGUNAKAN METODE GOAL PROGRAMMING

2018 ◽  
Vol 15 (1) ◽  
pp. 77-85 ◽  
Author(s):  
B Hidaen ◽  
A I Jaya ◽  
Resnawati Resnawati
Keyword(s):  
Goal Programming ◽  
Programming Model ◽  
Volume Distribution ◽  
Research Results ◽  
Distribution Costs ◽  
Goal Programming Model ◽  
The Cost ◽  
Distribution Cost

PT.Sinar Niaga Sejahtera isone ofdistributorin Palu who distribute products to a variety of shops. Goal Programming is a method that can solve the problem with more than one purposes. The purposes of this study are  to maximize the number of the car and minimize the distribution  cost of  PT.Sinar Niaga Sejahtera. Goal Programming model formulationin this research consistsof 6 priorities and 6 function constraints. The sixth priorities are,warehous capacity, the number of cars used to the distribution of goods to store Sinar Kasih II,store Cahaya Indah, store Bintang  Rezeki, store Hi. Abdullah, and a minimum distribution costs. Constraint functions consist of a number of cars and the cost of distribution. The research results showed that the supply of goods by the warehouse capacity that can fulfiil the necessary distribution of goods during the month amounted to 136.93 or 8.628 box Optimal volume distribution of goods in each store are sequentially Sinar Kasih II which is 2 units with a capacity of 4  or 252 box, Cahaya Indah 3 units with a capacity of 7  or 441 box, Hi. Abdullah 2 units with a capacity of 12 or 756 box and Star 2 cars Rezeki capacity of 4 . This model can save the distribution costs of Rp. 7.127.147 from the previous distribution costs of Rp. 35.000.000.

Optimizing Method of Express Delivery Network and Vehicle Routes Based on Automatic Parcel Machine

2014 ◽  
Vol 496-500 ◽  
pp. 2912-2916
Author(s):  
Yun Mei Qin ◽  
Hai Jun Mao ◽  
Yu Hui Li
Keyword(s):  
Delivery System ◽  
Optimization Problem ◽  
Clustering Algorithm ◽  
Programming Model ◽  
Delivery Mode ◽  
Dynamic Clustering ◽  
Practical Application ◽  
Mathematical Programming Model ◽  
Saving Algorithm ◽  
Express Delivery

An express delivery mode based on automatic parcel machine (APM) is put forward and the delivery system is optimized in this paper. The optimization problem is described as a mathematical programming model, and the improved twice dynamic clustering algorithm and the C-W saving algorithm are developed for solving it. Obtained results show that the mode and the express delivery system have great practical application value and popularized significance.

Route selection for best distances in road databases based on drivers’ and customers’ preferences

2012 ◽  
Vol 42 (6) ◽  
pp. 1126-1140 ◽  
Author(s):  
P. Flisberg ◽  
B. Lidén ◽  
M. Rönnqvist ◽  
J. Selander
Keyword(s):  
Integer Programming ◽  
Shortest Path ◽  
Optimization Model ◽  
Programming Model ◽  
Mixed Integer ◽  
Route Selection ◽  
Speed Limits ◽  
Online System ◽  
Selection For ◽  
National Road

The importance of road databases for distance calculations and route selection is increasing. One reason is that payments and invoicing are often based on the distance driven. However, it can be hard to agree on a “best” distance because of drivers’ preferences. These preferences can be described by road features such as road length, quality, width, speed limits, etc. Moreover, a pure standard “shortest path”, which is often used in road databases, can result in a route that is considerably shorter than a preferred and agreed distance. Consequently, there is a need to find suitable weights for the features of the roads that provide fair and agreed distances at the same time for all users. We propose an approach to find values of such weights for the features. The optimization model to find weights is an inverse shortest path problem formulated in a mixed integer programming model. The approach is tested for the Swedish Forestry National Road database. Since 2010, it has been in daily use to establish distances and is available for all forestry companies and haulers in Sweden through an online system.

scholarly journals Optimasi Jumlah Produksi dan Biaya Distribusi UMKM Semprong Amoundy Menggunakan Metode Simpleks dan Algoritma Greedy

2021 ◽  
Vol 5 (1) ◽  
pp. 9
Author(s):  
Resa Nofatiyassari ◽  
Rianita Puspa Sari
Keyword(s):  
Travelling Salesman Problem ◽  
Optimal Solution ◽  
Production Optimization ◽  
Production Costs ◽  
Travelling Salesman ◽  
Optimal Amount ◽  
Distribution Costs ◽  
House Production ◽  
Distribution Cost ◽  
The Greedy Algorithm

Production optimization must be considered in order to get the optimal amount of production, which is related to company profit. In addition, the distribution route that is not optimal will also cause production costs to expand. These two things are the main problems faced by Semprong Amoundy MSMEs that have not paid attention to optimization of production and optimization of distribution routes. The purpose of this research is to find the optimal solution of the number and type of semprong production to maximize the income of Amoundy MSMEs, and to find a solution for the shortest distribution route to minimize distribution costs of semprong products. The method used to solve this problem is Simplex Method and Travelling Salesman Problem with the Greedy Algorithm approach. The research resulted the decision that Amoundy MSMEs had to produce 18 boxes of large packaged semprong every day to generate maximum income. The distribution route that must be taken to minimize distribution costs is Amoundy House Production – Bontot Delajaya Shop – Erik Shop – Denpasar Shop – Aneka Shop – Oleh-oleh Karawang Outlet – Amoundy House Production, estimated distribution cost of Rp. 20.120,-.Optimasi produksi perlu diperhatikan agar didapatkan jumlah produksi yang optimal, yang mana hal ini akan berhubungan dengan profit perusahaan. Selain itu rute distribusi yang belum optimal juga akan menyebabkan pembengkakan biaya produksi. Kedua hal ini merupakan masalah utama yang dihadapi oleh UMKM Semprong Amoundy yang belum memperhatikan optimasi produksi dan optimasi rute distribusi. Tujuan dilakukannya penelitian ini yaitu untuk mencari solusi optimal dari jumlah dan jenis produksi semprong untuk memaksimalkan pendapatan UMKM Amoundy, serta mencari solusi rute distribusi terpendek untuk meminimalkan biaya pendistribusian produk semprong. Metode yang digunakan untuk adalah Metode simpleks dan  Travelling Salesman Problem dengan pendekatan algoritma greedy. Penelitian menghasilkan keputusan bahwa UMKM Amoundy harus memproduksi 18 box kue semprong kemasan besar setiap hari untuk menghasilkan pendapatan maksimal. Rute distribusi yang harus ditempuh untuk meminimalkan biaya distribusi yaitu Rumah Produksi Amoundy – Toko Bontot Delajaya – Toko Erik – Toko Denpasar – Toko Aneka – Outlet Oleh-oleh Karawang – Rumah Produksi Amoundy dengan taksiran biaya distribusi sebesar Rp. 20.120,-.

scholarly journals Penentuan Jalur Rute Distribusi Produk Fast Moving Consumer Goods (FMCG) dengan Menggunakan Metode Nearest Neighbour (Studi Kasus: PT.XYZ)

2019 ◽  
Vol 5 (2) ◽  
pp. 101
Author(s):  
Chendrasari Wahyu Oktavia ◽  
Christine Natalia ◽  
Indra Adigunawan
Keyword(s):  
Nearest Neighbor ◽  
Actual Data ◽  
Nearest Neighbour ◽  
Average Percentage ◽  
Distribution Costs ◽  
Logistics Company ◽  
Distribution Process ◽  
Total Travel Time ◽  
The Right ◽  
Distribution Cost

<p><em>Abstrak </em><strong>- PT. XYZ merupakan perusahaan logistik yang bergerak dalam pendistribusian produk ke seluruh area JABODETABEK. Dalam menjalankan aktivitas proses pendistribusian, perusahaan dihadapkan pada kondisi permasalahan yaitu perusahaan diharuskan untuk mengunjungi dan melayani konsumen dengan lokasi yang tersebar di area JABODETABEK dengan tetap memperhatikan kapasitas muatan dari armada dan rute yang dilalui kendaraan. Oleh karena itu, diperlukan penentuan rute yang tepat agar perusahaan dapat memenuhi pengiriman tepat waktu kepada konsumen. Dengan adanya masalah tersebut, penelitian ini bertujuan untuk melakukan optimasi rute kendaraan dengan metode <em>nearest neighbor</em> agar mampu meminimalisir total jarak, total waktu </strong><strong>dan biaya </strong><strong>distribusi </strong><strong>yang kemudian akan</strong><strong> </strong><strong>dianalisa </strong><strong>perbandingan data aktual dan <em>nearest neighbor</em>. </strong><strong>Pada penelitian ini menggunakan </strong><strong>metode <em>nearest neighbor</em>. Hasil yang didapatkan dari penelitian ini</strong><strong> adalah: </strong><strong>(</strong><strong>1</strong><strong>)</strong><strong> </strong><strong>M</strong><strong>ampu mengurangi persentase</strong><strong> rata-rata </strong><strong>jarak tempuh kendaraan dalam bulan Oktober 2018 sebesar 27%</strong><strong> atau 44,09 km tiap harinya,</strong><strong> </strong><strong>(</strong><strong>2</strong><strong>)</strong><strong> </strong><strong>Mengurangi total waktu tempuh 157 menit dari data aktual, (3) </strong><strong>M</strong><strong>ampu </strong><strong>menghemat</strong><strong> total biaya sebesar 15%</strong><strong> atau </strong><strong>Rp. 53,458</strong><strong> tiap harinya</strong><strong>. Dengan demikian metode pendekatan <em>nearest neighbor</em> mampu mengurangi biaya distribusi yang dikeluarkan oleh perusahaan tiap bulan.</strong></p><p><em>Abstract</em> – <strong>PT. XYZ is a logistics company engaged in the distribution of products throughout the Greater Jakarta area. In carrying out the distribution process activities, the company is faced with the requirements of the problem about the company required to provide information and serve consumers with locations scattered in the Greater Jakarta area with due regard to capacity of vehicle and route. Therefore, it is necessary to determine the right route so that companies can meet timely deliveries to consumers. Given these problems, this study aims to optimize vehicle routes with the nearest neighbor method so as to minimize the time and cost of distribution which will then be analyzed to analyze the actual data and the nearest neighbors. In this study using the nearest neighbor method. The results obtained from this study are: (1) Able to reduce the average percentage of vehicle mileage in October 2018 by 27% or 44,09 km per shipment. (2) reduce total travel time of 157 minute from actual data, (3) Able to increase total costs by 15% or Rp. 53,458. Thus,the method of taking the nearest neighbor can reduce the distribution costs incurred by the company each month.</strong></p><p><strong><em>Keywords</em></strong> – <em>Distribution cost, Nearest neighbor, Route determination</em><strong></strong></p>

Advances in the Use of Spaceborne InSAR for Application to Pipeline Route Selection and Integrity Management

2004 ◽  
Author(s):  
Corey R. Froese ◽  
Marco van der Kooij ◽  
Keith Kosar
Keyword(s):  
Ground Subsidence ◽  
Archival Data ◽  
Route Selection ◽  
Movement Rates ◽  
Ground Movements ◽  
Long Time ◽  
Integrity Management ◽  
Pipeline Route ◽  
Time Periods ◽  
Ongoing Monitoring

Spaceborne Synthetic Aperature Radar (InSAR) is a technique that has been used to measure ground movements associated with slope movements and subsidence since the mid-90’s. Previous applications had utilized either dry terrain with no vegetation cover or have relied on the use of articial targets to quanitify deformations. Recent advances in the processing technology have allowed for sub-millimetre level accuracy movements tracking over long time periods and for detection of movements as small as 2 mm/month in vegetated slopes in northern Canada. The archival data and the active aquisitions allow engineers working in the pipeline industry to both review previous movement rates and patterns for planning of pipeline routes and provides a tool for ongoing monitoring of deformations due to ground subsidence or slope movement for operational pipelines.

Low-carbon VRP for cold chain logistics considering real-time traffic conditions in the road network

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Qinyang Bai ◽  
Xaioqin Yin ◽  
Ming K. Lim ◽  
Chenchen Dong
Keyword(s):  
Road Network ◽  
Cold Chain ◽  
Time Varying ◽  
Low Carbon ◽  
Content Type ◽  
Distribution Costs ◽  
The Road ◽  
Traffic Conditions ◽  
Real Time Traffic ◽  
Distribution Cost

PurposeThis paper studies low-carbon vehicle routing problem (VRP) for cold chain logistics with the consideration of the complexity of the road network and the time-varying traffic conditions, and then a low-carbon cold chain logistics routing optimization model was proposed. The purpose of this paper is to minimize the carbon emission and distribution cost, which includes vehicle operation cost, product freshness cost, quality loss cost, penalty cost and transportation cost.Design/methodology/approachThis study proposed a mathematical optimization model, considering the distribution cost and carbon emission. The improved Nondominated Sorting Genetic Algorithm II algorithm was used to solve the model to obtain the Pareto frontal solution set.FindingsThe result of this study showed that this model can more accurately assess distribution costs and carbon emissions than those do not take real-time traffic conditions in the actual road network into account and provided guidance for cold chain logistics companies to choose a distribution strategy and for the government to develop a carbon tax.Research limitations/implicationsThere are some limitations in the proposed model. This study assumes that there are only one distribution and a single type of vehicle.Originality/valueExisting research on low-carbon VRP for cold chain logistics ignores the complexity of the road network and the time-varying traffic conditions, resulting in nonmeaningful planned distribution routes and furthermore low carbon cannot be discussed. This study takes the complexity of the road network and the time-varying traffic conditions into account, describing the distribution costs and carbon emissions accurately and providing the necessary prerequisites for achieving low carbon.

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