The Optimization Model and its Algorithms for Multiple Transportation Modes Selection in the Fourth Party Logistics

Li, Gui Hua; Huang, Min

doi:10.4028/www.scientific.net/amr.383-390.2249

Cited by 4 publications

(3 citation statements)

References 1 publication

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“…The main purpose of this paper is to solve the 4PLRP. There are three key issues, (1) Li and Huang (2015) design a maximum and minimum ant system for a fourth-party logistics routing optimization problem. Tao (2016) propose a column generation approach combined with graph search heuristic to efficiently solve the 4PLRP.…”

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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Section: Literature Reviewmentioning

confidence: 99%

4PL routing problem using hybrid beetle swarm optimization

Chen

Feng

et al. 2023

Soft Comput

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“…In the establishment of mathematical models, many studies regard the objective function of transportation cost and transportation time to reduce enterprise costs and improve customer satisfaction. For example, Li and Huang 7 mainly studied the problem of minimum total cost under multiple transportation mode selections in 4pl. Deng et al 8 proposed a route optimization model that minimizes the total cost under centralized and decentralized mixed transport modes.…”

Section: Introductionmentioning

confidence: 99%

Queuing theory-based optimization research on the multi-objective transportation problem of fourth party logistics

Hong

Liu

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part B:

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Fourth party logistics is an urgent need for economic and social development, and its research focuses on path optimization. Comprehensively considering the choice of third party logistics suppliers, routes, and transportation modes, this study proposes a multi-objective transportation optimization model based on queuing theory, which minimizes cost, time, and carbon emissions. In addition, to solve the problems of infeasible solutions in fourth party logistics route optimization (4plrp), a priority-random based strengthen elitist genetic algorithm is proposed. Experiments show that the algorithm has good convergence and stability in solving small/large 4plrp and is superior to six typical algorithms, such as the elite genetic algorithm.

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“…Cui et al [10] and Huang et al [25] studied the 4PLRP with fuzzy duration time. Li and Huang [32] worked on the multiple transportation modes selection problem in the 4PLRP.…”

Section: Introductionmentioning

confidence: 99%

Model and algorithm for 4PLRP with uncertain delivery time

Huang

Ren

Lee

et al. 2016

Information Sciences

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a b s t r a c tTo address the challenge of logistics routing decision under uncertain environment, this paper studies a fourth party logistics routing problem (4PLRP) with uncertain delivery time (4PLRPU). A novel 4PLRPU model based on uncertainty theory is proposed by describing the delivery time of a third party logistics (3PL) provider as an uncertain variable. After that, the model is transformed into an equivalent deterministic model, and several improved genetic algorithms are designed to get solutions. To handle the problem of infeasible solutions in the proposed 4PLRPU, an improved node-based genetic algorithm (INGA) and an improved distance-based genetic algorithm (IDGA) are developed to reduce the computing time required to repair infeasible solutions, and an improved genetic algorithm based on the simple graph and Dijkstra algorithm (SDGA) is proposed to avoid the generation of infeasible solutions. Numerical experiments are conducted to investigate the performance of the proposed algorithms and verify the effectiveness of the proposed 4PLRPU model. The results show that INGA and SDGA are more effective than the standard genetic algorithm and IDGA at solving large-scale problems. Additionally, compared with the expected value model, the 4PLRPU model is more robust.

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The Optimization Model and its Algorithms for Multiple Transportation Modes Selection in the Fourth Party Logistics

Cited by 4 publications

References 1 publication

4PL routing problem using hybrid beetle swarm optimization

4PL routing problem using hybrid beetle swarm optimization

Queuing theory-based optimization research on the multi-objective transportation problem of fourth party logistics

Model and algorithm for 4PLRP with uncertain delivery time

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