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 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.

scholarly journals A Hybrid Dynamic Programming for Solving Fixed Cost Transportation with Discounted Mechanism

2016 ◽  
Vol 2016 ◽  
pp. 1-9
Author(s):  
Farhad Ghassemi Tari
Keyword(s):  
Dynamic Programming ◽  
Programming Model ◽  
Transportation Network ◽  
Dynamic Programming Algorithm ◽  
Optimal Solution ◽  
Transportation Cost ◽  
Solution Algorithm ◽  
Transportation Costs ◽  
Programming Algorithm ◽  
Fixed Cost

The problem of allocating different types of vehicles for transporting a set of products from a manufacturer to its depots/cross docks, in an existing transportation network, to minimize the total transportation costs, is considered. The distribution network involves a heterogeneous fleet of vehicles, with a variable transportation cost and a fixed cost in which a discount mechanism is applied on the fixed part of the transportation costs. It is assumed that the number of available vehicles is limited for some types. A mathematical programming model in the form of the discrete nonlinear optimization model is proposed. A hybrid dynamic programming algorithm is developed for finding the optimal solution. To increase the computational efficiency of the solution algorithm, several concepts and routines, such as the imbedded state routine, surrogate constraint concept, and bounding schemes, are incorporated in the dynamic programming algorithm. A real world case problem is selected and solved by the proposed solution algorithm, and the optimal solution is obtained.

scholarly journals Carbon Emission Reduction of Apparel Material Distribution Based on Multi-Objective Genetic Algorithm (NSGA-II)

2019 ◽  
Vol 11 (9) ◽  
pp. 2571
Author(s):  
Xujing Zhang ◽  
Lichuan Wang ◽  
Yan Chen
Keyword(s):  
Genetic Algorithm ◽  
Carbon Emissions ◽  
Optimal Solution ◽  
Material Distribution ◽  
Low Carbon ◽  
Nsga Ii ◽  
Management Objectives ◽  
Multi Objective Genetic Algorithm ◽  
Distribution Process ◽  
The Cost

Low-carbon production has become one of the top management objectives for every industry. In garment manufacturing, the material distribution process always generates high carbon emissions. In order to reduce carbon emissions and the number of operators to meet enterprises’ requirements to control the cost of production and protect the environment, the paths of material distribution were analyzed to find the optimal solution. In this paper, the model of material distribution to obtain minimum carbon emissions and vehicles (operators) was established to optimize the multi-target management in three different production lines (multi-line, U-shape two-line, and U-shape three-line), while the workstations were organized in three ways: in the order of processes, in the type of machines, and in the components of garment. The NSGA-II algorithm (non-dominated sorting genetic algorithm-II) was applied to obtain the results of this model. The feasibility of the model and algorithm was verified by the practice of men’s shirts manufacture. It could be found that material distribution of multi-line layout produced the least carbon emissions when the machines were arranged in the group of type.

Insights to optimise marketing decisions on pig-grower farms

2019 ◽  
Vol 59 (6) ◽  
pp. 1126 ◽  
Author(s):  
S. V. Rodríguez-Sanchez ◽  
L. M. Pla-Aragones ◽  
R. De Castro
Keyword(s):  
Weight Control ◽  
Time Window ◽  
Programming Model ◽  
Transportation Cost ◽  
Management Policy ◽  
Mixed Integer ◽  
Factors Affecting ◽  
Pig Production ◽  
Marketing Policy ◽  
Feeding Program

Modern pig production in a vertically integrated company is a highly specialised and industrialised activity, requiring increasingly complex and critical decision-making. The present paper focuses on the decisions made on the pig-grower farms operating on an all-in–all-out management policy at the last stage of pig production. Based on a mixed-integer linear-programming model, an assessment for specific parameters to support marketing decisions on farms without individual weight control is made. The analysis of several key factors affecting the optimal marketing policy, such as transportation cost, when and how many pigs to deliver to the abattoir and weight homogeneity of the batch, served to gain insight into marketing decisions. The results confirmed that not just the feeding program, but also the grading price system, transportation and batch homogeneity have an enormous impact on the optimal marketing policy of fattening farms in a vertically integrated company. In addition, within the range of conditions considered, a time window of 4 weeks was deemed as optimal for delivering animals to the abattoir and the subsequent revenue was 15% higher than with traditional marketing rules.

scholarly journals A Synchronous Optimization Model for Multiship Shuttle Tanker Fleet Design and Scheduling Considering Hard Time Window Constraint

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Zhenfeng Jiang ◽  
Dongxu Chen ◽  
Zhongzhen Yang
Keyword(s):  
Time Window ◽  
Programming Model ◽  
Transportation Cost ◽  
Exact Algorithm ◽  
Mixed Integer ◽  
Routing Problem ◽  
Hard Time ◽  
Proposed Model ◽  
Total Transportation Cost ◽  
Time Window Constraints

A Synchronous Optimization for Multiship Shuttle Tanker Fleet Design and Scheduling is solved in the context of development of floating production storage and offloading device (FPSO). In this paper, the shuttle tanker fleet scheduling problem is considered as a vehicle routing problem with hard time window constraints. A mixed integer programming model aiming at minimizing total transportation cost is proposed to model this problem. To solve this model, we propose an exact algorithm based on the column generation and perform numerical experiments. The experiment results show that the proposed model and algorithm can effectively solve the problem.

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.

scholarly journals PENDISTRIBUSIAN PRODUK DENGAN VOGEL ‘S APPROXIMATION METHOD (VAM) DAN MODIFIED DISTRIBUTION METHOD (MODI) PENDISTRIBUSIAN PRODUK DENGAN VOGEL ‘S (VAM) DAN MODIFIED DISTRIBUTION METHOD (MODI)

2017 ◽  
Author(s):  
Tri Tri Hernawati
Keyword(s):  
Approximation Method ◽  
Minimum Cost ◽  
Transportation Cost ◽  
Initial Solution ◽  
Final Solution ◽  
Distribution Method ◽  
Initial Cost ◽  
Cost Distribution ◽  
Distribution Cost

AbstractThe research is aimed at analyzing the implementation of distribution transportation method and finding out the saving of distribution transportation cost by using Vogel’s Approximation Method and Modified Distribution Method (MODI). The research used Vogel’s Approximation Method as the initial solution and Modified Distribution Method as the final solution to save distribution transportation cost. Implementation of combination, Vogel’s Approximation Method and Modified Distribution Method is a system will be develop to find the results of calculation of the initial cost of distribution, a minimum cost distribution, and allocation of items to be distributed from the origin place to the destination place. Entry data by user is origin place (many place and name of place), destination place (many place and name of place), amount of supply from the each origin, amount of demand from the each destination, and distribution cost from the each origin to the each destination. The result of the research shows minimalizing total distribution cost about 10,7%

Research on Integrated Transportation of the Vehicle Logistics

2014 ◽  
Vol 945-949 ◽  
pp. 3287-3290
Author(s):  
Wen Li Tian ◽  
Cheng Xuan Cao
Keyword(s):  
Programming Model ◽  
Capacity Constraints ◽  
Time Constraint ◽  
Transportation Costs ◽  
Transportation Mode ◽  
Logistics Industry ◽  
Transport Mode ◽  
Searching Method ◽  
Inappropriate Choice ◽  
Future Reference

This paper focuses on the high transportation costs problem of the finished vehicle existing in the current vehicle logistics industry, which results from the inappropriate choice of the transport mode. Firstly, we establish a 0-1 programming model to select the integrated transportation mode quantitatively; Secondly, we solve the model by searching method which based on time constraint and capacity constraints; Finally, a case about the selection and optimization of the finished vehicles’ transportation mode in Anji Automotive Logistics Co.,Ltd are introduced to verify the model. The case results indicate that in the premise of meeting the requirement of time, the integrated transportation can greatly reduce the total transportation costs, which have significant implications for future reference in the choice of finished vehicle transportation.

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