The Fourth-Party Logistics Routing Problem Using Ant Colony System-Improved Grey Wolf Optimization

Lu, Fuqiang; Feng, Wenjing; Gao, Mengying; Bi, Hualing; Wang, Suxin

doi:10.1155/2020/8831746

Cited by 26 publications

(18 citation statements)

References 15 publications

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“…The contact history of a node is one component used in the probability calculation. Prediction-based techniques include [11][12][13][14][15][16] as examples. The third routing approach in ICNs is social-based.…”

Section: Data Exchange Methodsmentioning

confidence: 99%

Mail Man Ferry: A Novel Routing Protocol in Intermittently Connected Networks

Altamimi

2023

Electronics

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As an important area for mobile wireless networks, Intermittently Connected Networks (ICNs) have received increasing attention in practice and research in recent years. The main goals of the ICN routing protocol are to maximize the delivery probability and to minimize the delivery delay. These challenges have been investigated in previously proposed protocols with an assumption of fully cooperating nodes. Node cooperation directly impacts ICN performance in terms of delivery probability and delay. However, node cooperation is not guaranteed because a cooperating node consumes its buffer size and energy, thereby highlighting the challenges of memory, computation, and energy efficiencies. This paper addresses the challenge of ensuring node cooperation by proposing a novel routing protocol called Mail Man Ferry (MMF). The new protocol includes a node credit mechanism that ensures the cooperation of the network nodes. Extensive simulations were executed to evaluate the proposed protocol. Varying values of node cooperation in ICNs were employed in the simulation tests. The evaluation shows exciting results in which Mail Man Ferry outperforms previously proposed ICN protocols.

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Section: Data Exchange Methodsmentioning

confidence: 99%

Mail Man Ferry: A Novel Routing Protocol in Intermittently Connected Networks

Altamimi

2023

Electronics

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“…Different scholars have studied the original problem from different angles. Lu et al [31] designed an ant colony system-improved grey wolf optimization (ACS-IGWO) to solve it. Zhou et al [32] studied a two-level vehicle distribution mode based on a time window and simultaneous pick-up, and they designed a variable neighborhood tabu search algorithm to solve it.…”

Section: Takeout Deliverymentioning

confidence: 99%

Order Distribution and Routing Optimization for Takeout Delivery under Drone–Rider Joint Delivery Mode

Lu,

Jiang,

et al. 2024

JTAER

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Order distribution and routing optimization of takeout delivery is a challenging research topic in the field of e-commerce. In this paper, we propose a drone–rider joint delivery mode with multi-distribution center collaboration for the problems of limited-service range, unreasonable distribution, high delivery cost, and tight time windows in the takeout delivery process. The model is constructed with the minimum delivery cost and the overall maximum customer satisfaction as the objective function, and a two-stage heuristic algorithm is designed to solve the model. In the first stage, Euclidean distance is used to classify customers into the regions belonging to different distribution centers, and the affinity propagation (AP) clustering algorithm is applied to allocate orders from different distribution centers. The second stage uses an improved tabu search algorithm for route optimization based on specifying the number of rider and drone calls. This paper takes China’s Ele.me and Meituan takeout as the reference object and uses the Solomon data set for research. The experimental results show that compared with the traditional rider delivery mode, the drone–rider joint delivery mode with multiple distribution center collaboration can effectively reduce the number of riders used, lower the delivery cost, and improve the overall customer satisfaction.

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“…The good performance in terms of the solution quality and computational efficiency of the approach is shown through extensive numerical experiments on various scales of test instances. Lu (2020) design An ant colony system-improved grey wolf optimization (ACS-IGWO) for the 4PLRP with risk preference. The ability of ACS-IGWO is tested in simulation experiments.…”

Section: Literature Reviewmentioning

confidence: 99%

4PL routing problem using hybrid beetle swarm optimization

Chen

Feng

et al. 2023

Soft Comput

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Considering the uncertainty of transportation time and cost due to seasonality and human factors, A multi-objective chance constrained programming model with minimum transportation time and cost was established. According to the characteristics of the problem, the beetle search algorithm with one beetle is changed into multiple beetles and Dijkstra algorithm is embedded, a hybrid beetle swarm optimization algorithm (HBSO) is designed to solve the problem, and the case analysis and algorithm analysis are made for three different examples. By adjusting the model parameters, the minimum objective function value under the combination of parameters is obtained. Under the three examples, the influence of the customer on the time and cost is different, and the impact on the whole logistics and transportation scheme is obtained. The Taguchi test was used to determine the optimal parameter combination of the HBSO under different node scales. The GA and PSO are embedded with Dijkstra algorithm, and are compared with HBSO to verify the optimization ability of the HBSO.

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The Fourth-Party Logistics Routing Problem Using Ant Colony System-Improved Grey Wolf Optimization

Cited by 26 publications

References 15 publications

Mail Man Ferry: A Novel Routing Protocol in Intermittently Connected Networks

Mail Man Ferry: A Novel Routing Protocol in Intermittently Connected Networks

Order Distribution and Routing Optimization for Takeout Delivery under Drone–Rider Joint Delivery Mode

4PL routing problem using hybrid beetle swarm optimization

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