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.

The Robust Vehicle Routing Problem with Time Window Assignments

2021 ◽  
Vol 55 (2) ◽  
pp. 395-413
Author(s):  
Maaike Hoogeboom ◽  
Yossiri Adulyasak ◽  
Wout Dullaert ◽  
Patrick Jaillet
Keyword(s):  
Travel Time ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Service Providers ◽  
Time Window ◽  
Time Windows ◽  
Branch And Cut ◽  
Optimal Time ◽  
Routing Problem ◽  
Solution Approach

In practice, there are several applications in which logistics service providers determine the service time windows at the customers, for example, in parcel delivery, retail, and repair services. These companies face uncertain travel times and service times that have to be taken into account when determining the time windows and routes prior to departure. The objective of the proposed robust vehicle routing problem with time window assignments (RVRP-TWA) is to simultaneously determine routes and time window assignments such that the expected travel time and the risk of violating the time windows are minimized. We assume that the travel time probability distributions are not completely known but that some statistics, such as the mean, minimum, and maximum, can be estimated. We extend the robust framework based on the requirements’ violation index, which was originally developed for the case where the specific requirements (time windows) are given as inputs, to the case where they are also part of the decisions. The subproblem of finding the optimal time window assignment for the customers in a given route is shown to be convex, and the subgradients can be derived. The RVRP-TWA is solved by iteratively generating subgradient cuts from the subproblem that are added in a branch-and-cut fashion. Experiments address the performance of the proposed solution approach and examine the trade-off between expected travel time and risk of violating the time windows.

scholarly journals Ant Colony Optimization for Multiple Pickup and Multiple Delivery Vehicle Routing Problem with Time Window and Heterogeneous Fleets

Logistics ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 28
Author(s):  
Phan Nguyen Ky Phuc ◽  
Nguyen Le Phuong Thao
Keyword(s):  
Ant Colony Optimization ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Large Scale ◽  
Service Providers ◽  
Time Window ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Delivery Vehicle ◽  
Routing Problem

This study focuses on solving the vehicle routing problem (VRP) of E-logistics service providers. In our problem, each vehicle must visit some pick up nodes first, for instance, warehouses to pick up the orders then makes deliveries for customers in the list. Each pickup node has its own list of more than one customers requiring delivery. The objective is to minimize the total travelling cost while real-world application constraints, such as heterogeneous vehicles, capacity limits, time window, driver working duration, etc. are still considered. This research firstly proposes a mathematical model for this multiple pickup and multiple delivery vehicle routing problem with time window and heterogeneous fleets (MPMDVRPTWHF). In the next step, the ant colony optimization algorithm is studied to solve the problem in the large-scale.

scholarly journals An Adaptive Memetic Algorithm for Dynamic Electric Vehicle Routing Problem with Time-Varying Demands

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Na Wang ◽  
Yihao Sun ◽  
Hongfeng Wang
Keyword(s):  
Vehicle Routing ◽  
Electric Vehicle ◽  
Vehicle Routing Problem ◽  
Memetic Algorithm ◽  
Dynamic Environment ◽  
Time Varying ◽  
Routing Problem ◽  
Battery Capacity ◽  
Encoding Strategy ◽  
Local Search Operator

Dynamic electric vehicle routing problem (DEVRP) is an extension of the electric vehicle routing problem (EVRP) into dynamic logistical transportation system such that the demand of customer may change over time. The routing decision of DEVRP must concern with the driving range limitation of electric vehicle (EV) in a dynamic environment since both load degree and battery capacity are variable according to the time-varying demands. This paper proposes an adaptive memetic algorithm, where a special encoding strategy, an adaptive local search operator, and an economical random immigrant scheme are employed in the framework of evolutionary algorithm, to solve DEVRP efficiently. Numeric experiments are carried out upon a series of test instances that are constructed from a stationary VRP benchmark. The computational results show that the proposed algorithm is more effective in finding high-quality solution than several peer algorithms as well as significant in improving the capacity of the routing plan of EVs in dynamic transportation environment.

A Hybrid Metaheuristic Algorithm for the Green Vehicle Routing Problem in the Dynamic Environment

2021 ◽  
Vol 12 (4) ◽  
pp. 28-46
Author(s):  
Elhassania Messaoud ◽  
Adiba El Bouzekri El Idrissi ◽  
Ahmed Elhilali Alaoui
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Dynamic Environment ◽  
Mathematic Model ◽  
Neighborhood Search ◽  
Large Neighborhood Search ◽  
Dynamic Vehicle Routing ◽  
Routing Problem ◽  
New Information ◽  
Carbon Dioxide Co2

The main goal of this research is to combine the dynamic vehicle routing problem (DVRP), in which new information is received along the day, and the green vehicle routing problem (GVRP), which determines the routes of vehicles to serve a set of customers, while minimizing the total amount of the greenhouse gas. In this study, the customers must be serviced at their locations by a set of vehicles in real time by minimizing the carbon dioxide CO2. For that, the authors present the technique employed to estimate the amount of CO2 emissions and integrate it into the proposed mathematic model. Then they develop the resolution approach based on ant colony optimization (ACO) algorithm and a large neighborhood search (LNS) algorithm. The effectiveness of this approach is tested on a set of the static and dynamic green problems instances.

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.

scholarly journals A Vehicle Routing Problem with Consideration of Green Transportation

2017 ◽  
Vol 7 (4) ◽  
pp. 89 ◽  
Author(s):  
Che-Fu Hsueh
Keyword(s):  
Vehicle Routing ◽  
Fuel Consumption ◽  
Vehicle Routing Problem ◽  
Service Providers ◽  
Environmental Cost ◽  
Fixed Costs ◽  
Routing Problem ◽  
Fuel Consumption Rate ◽  
Logistics Company ◽  
Fuel Consumption And Emissions

This study aims to investigate the Green Vehicle Routing Problem (GVRP), which considers stochastic traffic speeds, so that fuel consumption and emissions can be reduced. Considering a heterogeneous fleet, the fuel consumption rate differs due to several factors, such as vehicle types and conditions, travel speeds, roadway gradients, and payloads. A mathematical model was proposed to deal with the GVRP, and its objective is to minimize the sum of the fixed costs and the expected fuel consumption costs. A customized genetic algorithm was proposed for solving the model. The computational experiments confirm the efficiency of the algorithm and show that the solution of GVRP is quite different from that of the traditional vehicle routing problem. We suggest that a company should use light vehicles to service the customers situated at higher terrains. The customers with higher demands can be visited earlier, but the customers situated at higher terrains or far away from the depot should be visited later. The study also found that the fixed costs of dispatching vehicles are critical in GVRP; a logistics company may thus tend to use large vehicles, despite that it may cause higher fuel consumption and emissions. The proposed model and algorithm are capable of suggesting a guidance for green logistics service providers to adopt a beneficial vehicle routing plan so as to eventually achieve a low economic and environmental cost.

scholarly journals SVND Enhanced Metaheuristic for Plug-In Hybrid Electric Vehicle Routing Problem

2020 ◽  
Vol 10 (2) ◽  
pp. 441 ◽  
Author(s):  
Xiaohui Li ◽  
Xuemin Shi ◽  
Yi Zhao ◽  
Huagang Liang ◽  
Yuan Dong
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Hybrid Electric Vehicle ◽  
Low Cost ◽  
Mixed Integer ◽  
Routing Problem ◽  
Routing Optimization ◽  
Planning Optimization ◽  
Battery Capacity ◽  
Hybrid Electric

Plug-in Hybrid Electric Vehicles (PHEVs), as a new type of environmental-friendly low cost transportation, have attracted growing interests for logistics. The path-planning optimization for PHEV has become a major challenge. In fact, PHEV-based routing optimization is a type of hybrid vehicle routing problem (HVRP). Compared with the traditional Traveling Salesman Problem (TSP) and Vehicle Routing Problem (VRP), the PHEV routing problem should consider more constraints, such as time limits, capacity constraints (including fuel tank capacity and battery capacity), electric stations, fuel stations and so forth. In this paper, a Mixed Integer Linear Programming formulation is presented and a novel hybrid metaheuristic approach (HMA_SVND) is proposed. Our method is a combination of memetic algorithm (MA), sequential variable neighborhood descent (SVND) and a revised 2_opt method. Comparative studies show that our proposed method outperformed previous works.

scholarly journals A Simheuristic Algorithm for Solving the Stochastic Omnichannel Vehicle Routing Problem with Pick-up and Delivery

Algorithms ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 237
Author(s):  
Leandro do C. Martins ◽  
Christopher Bayliss ◽  
Pedro J. Copado-Méndez ◽  
Javier Panadero ◽  
Angel A. Juan
Keyword(s):  
Vehicle Routing ◽  
Information And Communication Technologies ◽  
Vehicle Routing Problem ◽  
Low Cost ◽  
Communication Technologies ◽  
Routing Problem ◽  
Stochastic Version ◽  
Constructive Heuristic ◽  
Information And Communication ◽  
Np Hardness

Advances in information and communication technologies have made possible the emergence of new shopping channels. The so-called ‘omnichannel’ retailing mode allows customers to shop for products online and receive them at home. This paper focuses on the omnichannel delivery concept for the retailing industry, which addresses the replenishment of a set of retail stores and the direct shipment of the products to customers within an integrated vehicle routing formulation. Due to its NP-Hardness, a constructive heuristic, which is extended into a biased-randomized heuristic and which is embedded into a multi-start procedure, is introduced for solving the large-sized instances of the problem. Next, the problem is enriched by considering a more realistic scenario in which travel times are modeled as random variables. For dealing with the stochastic version of the problem, a simheuristic algorithm is proposed. A series of computational experiments contribute to illustrate how our simheuristic can provide reliable and low-cost solutions under uncertain conditions.

scholarly journals Optimization for medical logistics robot based on model of traveling salesman problems and vehicle routing problems

2021 ◽  
Vol 18 (3) ◽  
pp. 172988142110225
Author(s):  
Hui Jin ◽  
Qingsong He ◽  
Miao He ◽  
Shiqing Lu ◽  
Fangchao Hu ◽  
...  
Keyword(s):  
Vehicle Routing ◽  
Traveling Salesman Problem ◽  
Vehicle Routing Problem ◽  
Order Picking ◽  
Traveling Salesman ◽  
Vehicle Routing Problems ◽  
Traveling Salesman Problems ◽  
Routing Problem ◽  
Problem Model ◽  
Route Length

Fast medicine dispensing system (FMDS) as a kind of medical logistic robot can dispense many drugs for one prescription at the same time. To guarantee the sustainability of drug dispensation, it is required that FMDS replenish drugs rapidly. The traditional order picking model (OPM) is difficult to meet the demand of prompt replenishment. To solve the problems of prolonged refilling route and inefficiency of drugs replenishment, a mixed refilling model based on multiple steps traveling salesman problem model (MTSPM) and vehicle routing problem model (VRPM) is proposed, and it is deployed in two circumstances of FMDS, including temporary replenishment mode (TRM) and concentrate replenishment mode (CRM). It not only meted the demand under different circumstances of drug replenishment but also shortened the refilling route significantly. First, the new pick sets were generated. Then, the orders of pick sets were optimized and the new paths were achieved. When the number of pickings is varied no more than 20, experiment results declared that the refilling route is the shortest by utilizing MTSPM when working under the TRM condition. Comparing MTSPM with OPM, the rate of refilling route length decreased up to 32.18%. Under the CRM condition, the refilling route is the shortest by utilizing VRPM. Comparing VRPM with OPM, the rate of refilling route length decreased up to 58.32%. Comparing VRPM with MTSPM, the rate of refilling route length has dropped more than 43.26%.

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