scholarly journals Logistics Distribution Location Algorithm Based on Improved Imperial Competition Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Kaituo Su
Keyword(s):  
Information Exchange ◽  
Distribution Network ◽  
Route Optimization ◽  
Local Optimum ◽  
Oil Consumption ◽  
Transportation Model ◽  
Network Location ◽  
Logistics Distribution ◽  
Location Algorithm ◽  
Vehicle Path

To solve the problems of warehouse explosion and delay of logistics distribution network under the sudden explosion of demand on “double 11” and “618,” this paper proposes a logistics distribution network location algorithm that can consider reliability, green environmental protection, and path optimization. Firstly, the transportation model of logistics distribution network location-route optimization is established. Under the condition that the transportation model satisfies the vehicle path reliability constraint, it can minimize the total cost, including logistics distribution cost, transportation oil consumption, and CO2 emission cost. This paper designs an improved imperial competition algorithm to solve it according to the characteristics of the transportation model. Firstly, the competition mechanism of “United Lian Heng” was introduced in the initial national stage, enhancing the information exchange and retaining the superior population. Secondly, in the process of empire assimilation, we can learn from the colonial rule strategy, which is gradually infiltrated and assimilated by all levels of the country to enhance the development ability of the algorithm. Finally, the algorithm designs a mechanism to judge and jump out of local optimum, so as to avoid “premature” affecting the optimization performance. The rationality of the model and the effectiveness of the improved imperial competition algorithm are verified by simulation experiments of different scales, while the influence of reliability level is analyzed. Experimental results show that the proposed method can effectively solve problems of different scales and maintain stable performance under different reliability levels. Moreover, its algorithm performance is better than that of the standard imperial competition algorithm.

scholarly journals A Customer Clustering Algorithm for Power Logistics Distribution Network Structure and Distribution Volume Constraints

2021 ◽  
Vol 15 ◽  
pp. 1051-1056
Author(s):  
Jianying Zhong ◽  
Jibin Zhu ◽  
Yonghao Guo ◽  
Yunxin Chang ◽  
Chaofeng Zhu
Keyword(s):  
Network Structure ◽  
Clustering Algorithm ◽  
Distribution Network ◽  
Distribution Volume ◽  
Distribution Center ◽  
Vehicle Scheduling ◽  
Route Optimization ◽  
Scheduling Optimization ◽  
Logistics Distribution ◽  
Center Location

Customer clustering technology for distribution process is widely used in location selection, distribution route optimization and vehicle scheduling optimization of power logistics distribution center. Aiming at the problem of customer clustering with unknown distribution center location, this paper proposes a clustering algorithm considering distribution network structure and distribution volume constraint, which makes up for the defect that the classical Euclidean distance does not consider the distribution road information. This paper proposes a logistics distribution customer clustering algorithm, which improves CLARANS algorithm to make the clustering results meet the constraints of customer distribution volume. By using the single vehicle load rate, the sufficient conditions for logistics distribution customer clustering to be solvable under the condition of considering the ubiquitous and constraints are given, which effectively solves the problem of logistics distribution customer clustering with sum constraints. The results state clearly that the clustering algorithm can effectively deal with large-scale spatial data sets, and the clustering process is not affected by isolated customers, The clustering results can be effectively applied to the distribution center location, distribution cost optimization, distribution route optimization and distribution area division of vehicle scheduling optimization.

Research on Vehicle Routing Optimization Based on Improved Ant Colony Algorithm

2013 ◽  
Vol 385-386 ◽  
pp. 1917-1920
Author(s):  
Rui Wang ◽  
Zai Tang Wang
Keyword(s):  
Vehicle Routing ◽  
Optimization Problem ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Route Optimization ◽  
Local Optimum ◽  
Evaporation Coefficient ◽  
Logistics Distribution ◽  
Routing Optimization ◽  
Vehicle Routing Optimization

This paper analyzes the domestic and international logistics distribution route optimization problem and the research status of ant colony algorithm, illustrates the problems existing in the logistics distribution now. It reflects the necessity to research on the vehicle routing optimization problem. In order to increasing the ant colony algorithm’s convergence speed and avoiding to fall into local optimum, we improve the pheromone evaporation coefficient and visibility to optimize the searching ability, which can avoid premature convergence and stagnation.

Distribution Network Planning Based on Multi-Island Group Strategy Genetic Algorithm

2014 ◽  
Vol 960-961 ◽  
pp. 964-968
Author(s):  
Si Qing Sheng ◽  
Shao Bo Yang
Keyword(s):  
Genetic Algorithm ◽  
Closed Loop ◽  
Distribution Network ◽  
Network Planning ◽  
Local Optimum ◽  
Planning Model ◽  
Slow Convergence ◽  
Group Strategy ◽  
Island Group ◽  
Distribution Network Planning

In view of faults which the traditional genetic algorithm (GA) have such as slow convergence speed and easy to fall into the local optimum. This paper put forward a genetic algorithm which is based on the multi-island group strategy, and applied it to the distribution network planning. The paper has established a planning model which takes the yearly comprehensive cost as objective function and discusses the repair methods of islands, solitary chain and closed-loop to meet with the requirements of grid radial. Finally, the proposed method is planning on a 54-node grid to prove the effectiveness of the algorithm and model.

scholarly journals Study of Wireless Sensor Network Location Algorithm and Data Collection Protocol

2016 ◽  
Vol 12 (10) ◽  
pp. 70 ◽  
Author(s):  
Weimin Han ◽  
Shijun Li ◽  
Weidong Li
Keyword(s):  
Data Collection ◽  
Cluster Head ◽  
Life Time ◽  
Network Location ◽  
Specific Analysis ◽  
Collection Data ◽  
Location Algorithm ◽  
Network Life Time ◽  
Zone Division ◽  
Meaningful Event

<p style="margin: 0in 0in 10pt;"><span style="font-size: small;"><span style="font-family: Times New Roman;"><span style="-ms-layout-grid-mode: line;">It is deduced that the network life time is inversely proportional to the zone area of the collection data that each sink is responsible for. That is to say, when the zone area in the charge of a sink is smaller, the average load of nodes distributed in this area and the energy consumption are smaller, while the network life time is longer. MSGP protocol is proposed, with several round cluster head candidate zones, fixed member zones and public zones being delimited to make approximately uniform clustering. The cluster head is responsible for collecting a meaningful event in the cluster, making data fusion and then forwarding it to sink. Multi-sinks move according to the zone division rules and the rule of free movement. Specific analysis is made from three aspects of data direction, single round data collection of sink, and network life time</span>.</span></span></p>

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