scholarly journals Integration of order picking and vehicle routing in a B2C e-commerce context

2017 ◽  
Vol 30 (4) ◽  
pp. 813-843 ◽  
Author(s):  
Stef Moons ◽  
Katrien Ramaekers ◽  
An Caris ◽  
Yasemin Arda
Keyword(s):  
Vehicle Routing ◽  
Order Picking

Vehicle routing analyses with integrated order picking and delivery problem under carbon cap and trade policy

2019 ◽  
Vol 43 (2) ◽  
pp. 223-243 ◽  
Author(s):  
Sanjay Jharkharia ◽  
Chiranjit Das
Keyword(s):  
Sensitivity Analysis ◽  
Trade Policy ◽  
Vehicle Routing ◽  
Carbon Footprint ◽  
Order Picking ◽  
Mixed Integer ◽  
Vehicle Speed ◽  
Cap And Trade ◽  
Content Type ◽  
Total Cost

Purpose The purpose of this study is to model a vehicle routing problem with integrated picking and delivery under carbon cap and trade policy. This study also provides sensitivity analyses of carbon cap and price to the total cost. Design/methodology/approach A mixed integer linear programming (MILP) model is formulated to model the vehicle routing with integrated order picking and delivery constraints. The model is then solved by using the CPLEX solver. Carbon footprint is estimated by a fuel consumption function that is dependent on two factors, distance and vehicle speed. The model is analyzed by considering 10 suppliers and 20 customers. The distance and vehicle speed data are generated using simulation with random numbers. Findings Significant amount of carbon footprint can be reduced through the adoption of eco-efficient vehicle routing with a marginal increase in total transportation cost. Sensitivity analysis indicates that compared to carbon cap, carbon price has more influence on the total cost. Research limitations/implications The model considers mid-sized problem instances. To analyze large size problems, heuristics and meta-heuristics may be used. Practical implications This study provides an analysis of carbon cap and price model that would assist practitioners and policymakers in formulating their policy in the context of carbon emissions. Originality/value This study provides two significant contributions to low carbon supply chain management. First, it provides a vehicle routing model under carbon cap and trade policy. Second, it provides a sensitivity analysis of carbon cap and price in the model.

scholarly journals A Study on Online Scheduling Problem of Integrated Order Picking and Delivery with Multizone Vehicle Routing Method for Online-to-Offline Supermarket

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Jun Zhang ◽  
Xueyan Zhang ◽  
Yanfang Zhang
Keyword(s):  
Vehicle Routing ◽  
Competitive Ratio ◽  
Online Algorithm ◽  
Optimal Algorithm ◽  
Order Picking ◽  
Order Fulfillment ◽  
Delivery Problem ◽  
Computation Efficiency ◽  
Routing Method ◽  
Vehicle Capacity

The online order fulfillment of online-to-offline (O2O) supermarket faces the challenge in how to pick orders from thousands of products on the supermarket shelves and deliver them to customers in different zones and locations by a vehicle routing method within the lowest cost and shortest time. It is critical to integrate the order picking and delivery processes and schedule them jointly with a coordinated manner. Thus, in this paper, we study the online integrated order picking and delivery problem with multizone routing method (IOPDP-MR) to minimize both the maximum delivery completion time and the total delivery cost. The online algorithm A is presented to solve the online problem and is proved to be 2 1 + Q v -competitive, where Q v is the vehicle capacity. Since it is difficult to get a lower competitive ratio theoretically, the numerical experiments are proposed to analyze the gaps by comparing the values of algorithm A with the ones of offline optimal algorithm A∗ under different situations. It can be inferred that the competitive ratio is less than 2.5 and the average flow time for customer orders is less than 30 minutes, which verifies the good performance in both computation efficiency and customer satisfaction of algorithm A.

scholarly journals Batch Order and Discrete Order Picking Integrated with Vehicle Routing Decisions

2021 ◽  
Vol 24 ◽  
pp. 60-67
Author(s):  
Gerrit Karel Janssens ◽  
Stef Moons ◽  
Katrien Ramaekers ◽  
An Caris
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Service Providers ◽  
Low Cost ◽  
Dynamic Environment ◽  
Order Picking ◽  
Routing Problem ◽  
Time Period ◽  
Online Shoppers ◽  
Business To Consumer

In a business-to-consumer (B2C) context, customers order more frequently and in smaller quantities, resulting in a high number of consignments. Moreover, online shoppers expect a fast and accurate delivery at low cost or even free. To survive in such a market, companies can no longer optimise individual supply chain processes, but need to integrate several activities. In this article, the integrated order picking-vehicle routing problem is analysed in an e-commerce environment. In previous research, a mathematical programming formulation has been formulated in literature but only small-size instances can be solved to optimality. Two picking policies are studied: discrete order picking and batch order picking. The influence of various problem contexts on the value of integration is investigated: a small picking time period, outsourcing to 3PL service providers, and a dynamic environment context.

An algorithm for the capacitated vehicle routing problem for picking application in manual warehouses

2019 ◽  
Author(s):  
Eleonora Bottani ◽  
Giorgia Casella ◽  
Caterina Caccia ◽  
Roberto Montanari
Keyword(s):  
Vehicle Routing ◽  
Traveling Salesman Problem ◽  
Vehicle Routing Problem ◽  
Order Picking ◽  
Traveling Salesman ◽  
Manhattan Distance ◽  
Routing Problem ◽  
Capacitated Vehicle Routing Problem ◽  
Termination Criteria ◽  
Capacitated Vehicle

Given that warehouses play a central role in modern supply chains, this study proposes the application of an algorithm for the capacitated vehicle routing problem (CVRP) based on the two-index vehicle flow formulation developed by Baldacci, Hadjiconstantinou, and Mingozzi (2004) for picking purposes in manual warehouses. The study of Theys et al. (2010) is first used to represent the warehouse using a Steiner traveling salesman problem (TSP). Then, a calculation of the picking tour’s length is obtained applying the Manhattan distance. Finally, the algorithm for the CVRP is solved through a cutting plane with the addition of termination criteria related to the capacity of picker. The study analyzes four different warehouse configurations, processing five picking list each. The analysis is carried out exploiting the commercial software MATLAB®, to determine the solution that minimize distance of the order picking tour. The results obtained in MATLAB® show the effectiveness of the chosen algorithm applied to the context of manual order picking.

Integrating order picking and vehicle routing decisions

4OR ◽  
2018 ◽  
Vol 17 (1) ◽  
pp. 109-110
Author(s):  
Stef Moons
Keyword(s):  
Vehicle Routing ◽  
Order Picking
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