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Using Improved Particle Swarm Optimization Algorithm for location problem of Drone Logistics Hub

Computers, Materials & Continua 2024年第1期78卷 935-957页

作者： Li Zheng Gang Xu Wenbin Chen School of Mathematics and Computer Sciences Nanchang UniversityNanchang330031China

Drone logistics is a novel method of distribution that will become *** advantageous location of the logistics hub enables quicker customer deliveries and lower fuel consumption,resulting in cost savings for the company’s transportation *** firms must discern the ideal location for establishing a logistics hub,which is challenging due to the simplicity of existing models and the intricate delivery *** simulate the drone logistics environment,this study presents a new mathematical *** model not only retains the aspects of the current models,but also considers the degree of transportation difficulty from the logistics hub to the village,the capacity of drones for transportation,and the distribution of logistics hub ***,this paper proposes an improved particle swarm optimization(PSO)algorithm which is a diversity-based hybrid PSO(DHPSO)algorithm to solve this *** DHPSO,the Gaussian random walk can enhance global search in the model space,while the bubble-net attacking strategy can speed ***,Archimedes spiral strategy is employed to overcome the local optima trap in the model and improve the exploitation of the *** maintains a balance between exploration and exploitation while better defining the distribution of logistics hub locations Numerical experiments show that the newly proposed model always achieves better locations than the current *** DHPSO with other state-of-the-art intelligent algorithms,the efficiency of the scheme can be improved by 42.58%.This means that logistics companies can reduce distribution costs and consumers can enjoy a more enjoyable shopping experience by using DHPSO’s location *** the results show the location of the drone logistics hub is solved by DHPSO effectively.

关键词： Drone logistics location problem mathematical model diversity particle swarm optimization

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location and allocation problem for spare parts depots on integrated logistics support

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Journal of Systems Engineering and Electronics 2019年第6期30卷 1252-1259页

作者： WEN Meilin LU Bohan LI Shuyu KANG Rui School of Reliability and Systems Engineering Beihang UniversityBeijing 100191China Science and Technology on Reliability and Environmental Engineering Laboratory Beijing 100191China

In equipment integrated logistics support(ILS), the supply capability of spare parts is a significant factor. There are lots of depots in the traditional support system, which makes too many redundant spare parts and causes high cost of support. Meanwhile,the inconsistency among depots makes it difficult to manage spare parts. With the development of information technology and transportation, the supply network has become more efficient. In order to further improve the efficiency of supply-support work and the availability of the equipment system, building a system of one centralized depot with multiple depots becomes an appropriate *** this case, location selection of the depots including centralized depots and multiple depots becomes a top priority in the support system. This paper will focus on the location selection problem of centralized depots considering ILS factors. Unlike the common location selection problem, depots in ILS require a higher service level. Therefore, it becomes desperately necessary to take the high requirement of the mission into account while determining location of depots. Based on this, we raise an optimal depot location model. First, the expected transportation cost is ***, factors in ILS such as response time, availability and fill rate are analyzed for evaluating positions of open depots. Then, an optimization model of depot location is developed with the minimum expected cost of transportation as objective and ILS factors as constraints. Finally, a numerical case is studied to prove the validity of the model by using the genetic algorithm. Results show that depot location obtained by this model can guarantee the effectiveness and capability of ILS well.

关键词： location problem spare parts depot integrated logis tics support genetic algorithm.

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A New Model for location problem with Stochastic Demands

A New Model for Location Problem with Stochastic Demands

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ICSSSM'04国际会议

作者： Juqi LIU Yueting CHAI Yi LIU Automation Department Tsinghua University Beijing 100084 China

＜正＞ This article proposes a new model which integrates the service level constraints （product available rate） and considers the uncertainty of customer demands at the same time. The customer demands are described with normal distribution functions. We try to locate the facilities and determine the customers assigned to them simultaneously. The goal is to minimize the total logistics cost and meet the specific constraints of product available rate at each facility. In order to describe the capacity constraints properly, we introduce chance constraints with confidence level β. Our problem is thus a strategic decision problem under uncertainty and can be viewed as an extension to the traditional capacitated location problem with fixed cost. We also present two hybrid intelligent algorithms to find the near-optimal solutions. Extensive computational results across a variety of problem structures are reported.

关键词： location problem stochastic demand Service level

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CHARGING STATION PLANNING FOR PLUG-IN ELECTRIC VEHICLES

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Journal of Systems Science and Systems Engineering 2018年第1期27卷 24-45页

作者： Zhihong Zhu Ziyou Gao Jianfeng Zheng Haoming Du Transportation Management College Dalian Maritime University Dalian China

A novel model for the charging station planning problem of plug-in electric vehicles is proposed in this paper considering the users＇ daily travel. With the objective of minimizing the total cost, including the charging stations＇ cost （including installing cost and management cost） and the users＇ cost （including station access cost and charging cost）, the proposed model simultaneously handles the problems where to locate the charging stations and how many chargers to be established in each charging station. Considering that different users may have different perception of station access cost and charging cost, two cases （i.e., homogeneous users and heterogeneous users） are typically investigated. The impacts of different discount rates, operating period of the charging stations, number of electric vehicles and number of charging stations on the location of the charging station are also studied. The simulation results not only show that it is very important to locate the charging stations according to the traveling behavior of users, but also verify the validity of the proposed model.

关键词： Electric vehicles charging station location problem

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