scholarly journals Urban Transportation Network Design for Fresh Fruit and Vegetables Using GIS–The Case of Bangkok

2019 ◽  
Vol 9 (23) ◽  
pp. 5048 ◽  
Author(s):  
Suraraksa ◽  
Shin
Keyword(s):  
Urban Areas ◽  
Transportation Network ◽  
Time Windows ◽  
Operating Cost ◽  
Distribution Networks ◽  
Cold Chain ◽  
Problem Analysis ◽  
Distribution Centers ◽  
Routing Problem ◽  
Fresh Products

A cold chain for perishable fresh products aims to preserve the quality of the products under the control of a predefined temperature range. To satisfy the delivery conditions within appropriate time windows, the most critical operations in cold chain management is the transportation and distribution of fresh products. Due to rapid population growth and increasing demand for high-quality fresh foods, it becomes critical to develop advanced transportation and distribution networks for fresh products, particularly in urban areas. This research aims to design different scenarios based on mathematical models for fresh products transportation and distribution network in the Bangkok metropolitan area using Geographic Information system (GIS). The proposed methodology integrates location–allocation and vehicle routing problem analysis. The performance of all possible scenarios is evaluated and compared by considering the number of required distribution centers and trucks, total travel time, total travel distance, as well as fairness among drivers. The results of the scenario analysis highlight that the alternative scenarios show a better performance as compared to the current network. In addition, the administrator can make a different decision among several alternatives by considering different aspects, such as investment cost, operating cost, and balance of using available resources. Therefore, it may help a public officer to design the fresh products logistics network considering actual demand and traffic conditions in Bangkok.

LIRP optimization of cold chain logistics in satellite warehouse mode of supermarket chains

2021 ◽  
pp. 1-15
Author(s):  
Bo Shu ◽  
Fanghua Pei ◽  
Kaifu Zheng ◽  
Mengxia Yu
Keyword(s):  
Time Windows ◽  
Home Delivery ◽  
Cold Chain ◽  
Inventory Routing ◽  
Logistics System ◽  
Routing Problem ◽  
Penalty Cost ◽  
Location Allocation ◽  
Soft Time Windows ◽  
Fresh Products

Aiming at the problem of high cost in cold chain logistics of fresh products home-delivery in supermarket chain in the new retail era, the paper constructs the model of Location Inventory Routing Problem (LIRP) optimization in Satellite Warehouse mode in view of customer satisfaction with the broken line soft time windows. The model minimizes the total cost of the cold chain logistics system of supermarket chain through the location allocation, inventory optimization, the determination of distribution service relationship between Satellite Warehouse and customer, and the constraint of time penalty cost. Then, the paper designed an improved ant colony optimization to solve the LIRP model of supermarket chain. Finally, the simulation in MATLAB verifies and analyzes the validity of the model and algorithm. Therefore, LIRP optimization model in Satellite Warehouse mode can effectively improve the operational efficiency of fresh products home-delivery in the supermarket chain and thus reduce the logistics cost.

scholarly journals Location Routing Problem with Consideration of CO2 Emissions Cost: A Case Study

2020 ◽  
Vol 21 (2) ◽  
pp. 225-234
Author(s):  
Ananda Noor Sholichah ◽  
Y Yuniaristanto ◽  
I Wayan Suletra
Keyword(s):  
Co2 Emissions ◽  
Time Windows ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Distribution Centers ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing ◽  
Study Results

Location and routing are the main critical problems investigated in a logistic. Location-Routing Problem (LRP) involves determining the location of facilities and vehicle routes to supply customer's demands. Determination of depots as distribution centers is one of the problems in LRP.  In LRP, carbon emissions need to be considered because these problems cause global warming and climate change. In this paper, a new mathematical model for LRP considering CO2 emissions minimization is proposed. This study developed a new  Mixed Integer Linear Programming (MILP)  model for LRP with time windows and considered the environmental impacts.  Finally, a case study was conducted in the province of Central Java, Indonesia. In this case study, there are three depot candidates. The study results indicated that using this method in existing conditions and constraints provides a more optimal solution than the company's actual route. A sensitivity analysis was also carried out in this case study.

scholarly journals Optimal vehicle route schedules in picking up and delivering cargo containers considering time windows in logistics distribution networks: A case study

2020 ◽  
Vol 26 (4) ◽  
pp. 174-184
Author(s):  
Thi Diem Chau Le ◽  
Duy Duc Nguyen ◽  
Judit Oláh ◽  
Miklós Pakurár
Keyword(s):  
Mathematical Model ◽  
Simulated Annealing ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Distribution Networks ◽  
Mixed Integer ◽  
Vehicle Group ◽  
Real Problem ◽  
Routing Problem

AbstractThis study describes a pickup and delivery vehicle routing problem, considering time windows in reality. The problem of tractor truck routes is formulated by a mixed integer programming model. Besides this, three algorithms - a guided local search, a tabu search, and simulated annealing - are proposed as solutions. The aims of our study are to optimize the number of internal tractor trucks used, and create optimal routes in order to minimize total logistics costs, including the fixed and variable costs of an internal vehicle group and the renting cost of external vehicles. Besides, our study also evaluates both the quality of solutions and the time to find optimal solutions to select the best suitable algorithm for the real problem mentioned above. A novel mathematical model is formulated by OR tools for Python. Compared to the current solution, our results reduced total costs by 18%, increased the proportion of orders completed by internal vehicles (84%), and the proportion of orders delivered on time (100%). Our study provides a mathematical model with time constraints and large job volumes for a complex distribution network in reality. The proposed mathematical model provides effective solutions for making decisions at logistics companies. Furthermore, our study emphasizes that simulated annealing is a more suitable algorithm than the two others for this vehicle routing problem.

Metaheuristics for solving the vehicle routing problem with the time windows and energy consumption in cold chain logistics

2020 ◽  
Vol 95 ◽  
pp. 106561 ◽  
Author(s):  
Mei-xian Song ◽  
Jun-qing Li ◽  
Yun-qi Han ◽  
Yu-yan Han ◽  
Li-li Liu ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Cold Chain ◽  
Routing Problem

scholarly journals Mathematical Formulation and Comparison of Solution Approaches for the Vehicle Routing Problem with Access Time Windows

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Rafael Grosso ◽  
Jesús Muñuzuri ◽  
Alejandro Escudero-Santana ◽  
Elena Barbadilla-Martín
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Urban Areas ◽  
Time Windows ◽  
Mathematical Formulation ◽  
Access Time ◽  
Routing Problem ◽  
Urban Freight ◽  
Additional Costs ◽  
Problem Instances

The application of the principles of sustainability to the implementation of urban freight policies requires the estimation of all the costs and externalities involved. We focus here on the case of access time windows, which ban the access of freight vehicles to central urban areas in many European cities. Even though this measure seeks to reduce congestion and emissions in the most crowded periods of the day, it also imposes additional costs for carriers and results in higher emissions and energy consumption. We present here a mathematical model for the Vehicle Routing Problem with Access Time Windows, a variant of the VRP suitable for planning delivery routes in a city subject to this type of accessibility restriction. We use the model to find exact solutions to small problem instances based on a case study and then compare the performance over larger instances of a modified savings algorithm, a genetic algorithm, and a tabu search procedure, with the results showing no clear prevalence of any of them, but confirming the significance of those additional costs and externalities.

scholarly journals ABM-GIS simulation for urban freight distribution of perishable food

2018 ◽  
Vol 200 ◽  
pp. 00006 ◽  
Author(s):  
Hanane El Raoui ◽  
Mustapha Oudani ◽  
Ahmed El Hilali Alaoui
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Scheduling Algorithm ◽  
Time Windows ◽  
Freight Transport ◽  
Time Dependent ◽  
Traffic Condition ◽  
Routing Problem ◽  
Urban Freight ◽  
The Impact

Freight transport is essential to modern urban civilization. No urban area could exist without a powerful freight transport system. However, the distribution of perishable foods in urban areas is seen as a source of problems, due to traffic congestion, time pressures, and environmental impact. In this paper, an Agent-Based Model integrated with Geographic Information Systems (ABM-GIS) is designed for a time-dependent vehicle routing problem with time windows. This simulation model consists of determining the quickest routes to transport fresh products, estimating Vehicle kilometer traveled VKT and vehicle hour traveled VHT where speeds and travel times depend on the time of the day. Based on a case study, analyses of changes on traffic condition were conducted to get an insight into the impact of these changes on cost, service quality represented by the respect of time windows, and carbon emissions. The results reveal that traffic jams and restrictive time windows lead to additional cost, cause delays, and increase co2 emission. As for a short-term planning, time-dependent scheduling algorithm was proposed and assessed while extending time windows. Results have proved the potential saving in cost, travel time, and carbon emission.

Network Optimization of Railway Cold Chain Logistics Based on Freight Subsidy

2021 ◽  
pp. 036119812110119
Author(s):  
Yu Lu ◽  
Xingfang Xu ◽  
Chuanzhong Yin ◽  
Yueyi Zhang
Keyword(s):  
Market Share ◽  
Network Optimization ◽  
Simulated Annealing Algorithm ◽  
Time Window ◽  
Carbon Tax ◽  
Transportation Network ◽  
Time Windows ◽  
Travel Speed ◽  
Cold Chain ◽  
Long Distance

The proportion of railway cold chain transportation in the overall cold chain logistics transportation market is relatively small in China. Freight subsidies and cold chain train operations are typically effective approaches to guide the public transit of cold chain cargo flow and grow the railway cold chain transportation market. We analyzed the cost structure of a cold chain transportation network. We established a network optimization model of the railway cold chain logistics based on a freight subsidy and designed an adaptive genetic–simulated annealing algorithm (A-SAGA). Taking the cold chain transportation between the Yangtze river delta urban agglomerations and the Chengdu–Chongqing city group as an example, we determined the optimal cold chain logistics transportation scheme using the traditional genetic algorithm and the A-SAGA. Moreover, we conducted sensitivity analysis on freight subsidies, train travel speeds, soft time windows, and carbon tax rates. The results showed that for medium- and long-distance cold chain transportation, the railway market share increased from 17.55% to 18.75% with an increase in the railway freight rate subsidy share from 0% to 30%. More cold chain goods were transported by rail when the soft time window or the carbon tax rate increased. Moreover, the railway market share increased from 17.55% to 43.75% with an increase in the train travel speed from 60 km/h to 120 km/h. Thus, compared with freight subsidy, increasing the train travel speed is a better approach to improve the competitiveness of railway cold chain logistics.

scholarly journals Two-Echelon Location-Routing Problem with Time Windows and Transportation Resource Sharing

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Yong Wang ◽  
Yaoyao Sun ◽  
Xiangyang Guan ◽  
Yanyong Guo
Keyword(s):  
Genetic Algorithm ◽  
Optimization Model ◽  
Resource Sharing ◽  
Hybrid Algorithm ◽  
Time Windows ◽  
Operating Cost ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Logistics Networks ◽  
Location Routing

In this work, a two-echelon location-routing problem with time windows and transportation resource sharing (2E-LRPTWTRS) is solved by selecting facility locations and optimizing two-echelon vehicle routes. The optimal solutions improve the efficiency of a logistics network based on the geographical distribution and service time windows of logistics facilities and customers. Furthermore, resource utilization is maximized by enabling resource sharing strategies within and among different logistics facilities simultaneously. The 2E-LRPTWTRS is formulated as a biobjective optimization model, and obtaining the smallest number of required delivery vehicles and the minimum total operating cost are the two objective functions. A two-stage hybrid algorithm composed of k-means clustering and extended multiobjective particle swarm optimization algorithm is proposed for 2E-LRPTWTRS optimization. A self-adaptive mechanism of flight parameters is introduced and adopted during the iterative process to balance the evolution of particles and improve the efficiency of the two-stage hybrid algorithm. Moreover, 20 small-scale instances are used for an algorithm comparison with multiobjective genetic algorithm and nondominated sorting genetic algorithm-II, and the solutions demonstrate the superiority of the proposed algorithm in optimizing logistics networks. The proposed optimization model and hybrid algorithm are tested by employing a real-world case of 2E-LRPTWTRS in Chongqing, China, and the optimization results verify the positive role of the developed model and algorithm in improving logistics efficiency, reducing operating cost, and saving transportation resources in the operations of two-echelon logistics networks.

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