Solving the vehicle routing problem with drone for delivery services using an ant colony optimization algorithm

Huang, Shan-Huen; Huang, Ying‐Hua; Blázquez, Carola; Chen, Chia-Yi

doi:10.1016/j.aei.2022.101536

Cited by 86 publications

(20 citation statements)

References 47 publications

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“…, 2004). Several researchers have incorporated ACO as a tool to determine decisions related to shortest path and delivery times (Huang et al. , 2022; Jia et al.…”

Section: Solution Methodologymentioning

confidence: 99%

“…This is primarily due to the characteristic of ACO algorithm that makes explicit use of elements of previous solutions to develop a constructive solution to include it in a population framework (Maniezzo et al, 2004). Several researchers have incorporated ACO as a tool to determine decisions related to shortest path and delivery times (Huang et al, 2022;Jia et al, 2022;Kounte et al, 2022). Due to this wide scale adoptability of ACO in the similar field, we also adopted an ACO based routing strategy for our study.…”

Section: Attended Home Deliverymentioning

confidence: 99%

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Attended home delivery under uncertain travel and response time: a case of Indian public distribution system

Chakraborty

Bagga

Sarmah

2022

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PurposeBeing the final end of the logistic distribution, attended home delivery (AHD) plays an important role in the distribution network. AHD typically refers to the service provided by the distribution service provider to the recipient's doorstep. Researchers have always identified AHD as a bottleneck for last-mile delivery. This paper addresses a real-life stochastic multi-objective AHD problem in the context of the Indian public distribution system (PDS).Design/methodology/approachTwo multi-objective models are proposed. Initially, the problem is formulated in a deterministic environment, and later on, it is extended to a multi-objective AHD model with stochastic travel and response time. This stochastic AHD model is used to extensively analyze the impact of stochastic travel time and customer response time on the total expected cost and time-window violation. Due to the NP-hard nature of the problem, an ant colony optimization (ACO) algorithm, tuned via response surface methodology (RSM), is proposed to solve the problem.FindingsExperimental results show that a change in travel time and response time does not significantly alter the service level of an AHD problem. However, it is strongly correlated with the planning horizon and an increase in the planning horizon reduces the time-window violation drastically. It is also observed that a relatively longer planning horizon has a lower expected cost per delivery associated.Research limitations/implicationsThe paper does not consider the uncertainty of supply from the warehouse. Also, stochastic delivery failure probabilities and randomness in customer behavior have not been taken into consideration in this study.Practical implicationsIn this paper, the role of uncertainty in an AHD problem is extensively studied through a case of the Indian PDS. The paper analyzes the role of uncertain travel time and response time over different planning horizons in an AHD system. Further, the impact of the delivery planning horizon, travel time and response time on the overall cost and service level of an AHD system is also investigated.Social implicationsThis paper investigates a unique and practical AHD problem in the context of Indian PDS. In the present context of AHD, this study is highly relevant for real-world applications and can help build a more efficient delivery system. The findings of this study will be of particular interest to the policy-makers to build a more robust PDS in India.Originality/valueThe most challenging part of an AHD problem is the requirement of the presence of customers during the time of delivery, due to which the probability of failed delivery drastically increases if the delivery deviates from the customer's preferred time slot. The paper modelled an AHD system to incorporate uncertainties to attain higher overall performance and explore the role of uncertainty in travel and response time with respect to the planning horizon in an AHD, which has not been considered by any other literature.

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“…, 2004). Several researchers have incorporated ACO as a tool to determine decisions related to shortest path and delivery times (Huang et al. , 2022; Jia et al.…”

Section: Solution Methodologymentioning

confidence: 99%

Section: Attended Home Deliverymentioning

confidence: 99%

Attended home delivery under uncertain travel and response time: a case of Indian public distribution system

Chakraborty

Bagga

Sarmah

2022

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“…The key objective is to optimize and synchronize the routes for the truck and the drone so that neither one needs to wait for the other and efficiency is maximized. The use of Ant Colony Optimizer was proposed as a solution for this optimization problem [33]. The ACO was able to find the optimal route, so that the truck's idling was minimized while waiting for the drone.…”

Section: Optimization Of Multiple Stop Distribution Routesmentioning

confidence: 99%

The Current State and Future of the Road Transport Based Cold Chain

Tuovinen,

Usvakangas,

Neittaanmäki

2024

Preprint

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Cold chains are essential in providing us humans with food and medicine across the globe. However, cold transportation, like all transportation, has massive negative impacts on the environment and human well-being, which especially culminate in cities. Thus, it is important to research the ways to reduce these impacts and reinvent urban logistics infrastructure. In this article, we articulate the massive problems the road-based transportation sector imposes on the environment and on the health of humans, especially in cities. We present algorithms that show promise in optimizing the whole road transportation sector as well as some innovations and alternative ways to model cities and the whole urban transportation infrastructure. We approach the issues discussed specifically from the point of view of refrigerated transportation, but many of the solutions can be applied to all the transportation sector in general.

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“…These two-dimensional solutions provide a suitable solution mostly for agricultural problems and patrol and monitoring tasks. The following algorithms are most often used by researchers during route planning suitable for inventory: the traditional squid algorithm [10]; the genetic algorithm [11,12]; the rapidly expanding random tree algorithm [13,14]; the traditional particle swarm optimization algorithm (PSO); the ant colony algorithm [15,16]; and deep neural networks [17,18]. Most of the research only uses the shortest flight path [19] or the least energy consumption [20] to generate the singleobjective optimization model, and further uses the convex approximation strategy [21] to calculate the route.…”

Section: Literature Reviewmentioning

confidence: 99%

A Path Planning Model with a Genetic Algorithm for Stock Inventory Using a Swarm of Drones

Gubán

Udvaros

2022

Drones

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In this paper, a mathematical model and solution for performing the inventory tasks of a multi-user, mixed warehouse in which neither satellite positioning nor other IT solutions can be used was presented. After reviewing the literature on road planning and the use of drones in warehouses, a method is presented that can be used to control drones that can be moved in all directions for imaging and transmission. The proposed method consists of three main steps. As a first step, we provide the mathematical model and solution method needed to determine the (optimal execution time) access routes required for processing the compartments of the warehouses. This is an initial step before starting the inventory. This considers the structure of the warehouse, its features, the number of drones, and the parameters of the drones. In the second step, based on the routes obtained in the first step, the real-time movement of the drones was controlled during processing, including camera movement and image recording. The third step is post-processing, i.e., processing the images for QR code identification, interpreting the QR code, and recognizing empty compartments for inventory control. A major advantage for users of the solution method is that the result can be achieved automatically without an external orientation device, relying solely on its own movement and the organization of a pre-planned route. The proposed model and solution method are suitable not only for inventory control, but also for solving other problems matching the model.

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Solving the vehicle routing problem with drone for delivery services using an ant colony optimization algorithm

Cited by 86 publications

References 47 publications

Attended home delivery under uncertain travel and response time: a case of Indian public distribution system

Attended home delivery under uncertain travel and response time: a case of Indian public distribution system

The Current State and Future of the Road Transport Based Cold Chain

A Path Planning Model with a Genetic Algorithm for Stock Inventory Using a Swarm of Drones

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