An Immunity-Based Algorithm for Distribution Center Location

2014 ◽  
Vol 971-973 ◽  
pp. 1537-1542
Author(s):  
Chao Ying Wang ◽  
Zhi Neng Liu

The distribution center is the bridge connected supply points and demand points, lies in pivotal status in modern logistics system. Firstly, the mathematical model of a distribution center location is established, based on the study of using neural network to solve distribution center location of the previous scholars, a new method is presented as well as the improved immune algorithm. A new affinity formula is designed for immunoselection criteria. Simultaneously, based on the mathematical model and cases, the algorithm is drilled concrete. A case shows that the improved immune algorithm can better solve the problem of the distribution center location.

2013 ◽  
Vol 756-759 ◽  
pp. 1366-1370
Author(s):  
Hong Li ◽  
Xiao Yu Liu ◽  
Jin Ping Zhang ◽  
Ya Long Yu

Logistics center is a mordern logistic facility. The distribution center location determines the operational efficiency of logistics system. The optimum location of distribution center is important to transportation. In order to improved the algorithm's efficiency, elite strategy was introduced based on the standard immune algorithm. The improved algorithm avoid trapping into local optimal solution and solving the problem more slowly. The role of the elite strategy is to make the optimal solution attractively in the next cycle. This method sovles problem both quantitatively and qualitatively, which makes final solution better in accordance with practical demands.


2021 ◽  
Vol 5 (2) ◽  
pp. 166-178
Author(s):  
Eva Kostikov ◽  
Petra Jílkova ◽  
Pavla Kotatkova Stranska

Since the COVID-19 pandemic hit last year, countries locked their borders. Thus, international shipping deteriorates drastically. Simultaneously, social distancing increased the need for immediate online consumption and fast home delivery. In the non-digital world, products still need to be shipped to their destination using trucks, trains, airplanes, and ships. Simultaneously, requirements for volumes of goods, transport costs, external limiting factors, etc., must be precisely defined. The article aims to find the optimal location selection solution based on the created mathematical model of the Modified Steiner-Weber Problem with restrictive conditions. The model allows for the central warehouse's optimal location and minimizes distribution costs from the central warehouse to sub-warehouses/branches located in individual EU countries. The mathematical model has been applied to a case study of a selected e-commerce dealing, which has established branches in capital cities but does not have an established central warehouse. Systematization of literature sources and approaches to solving the problem of e-commerce distribution center location showed that 86% of the studied companies plan to use on-demand warehousing in the next three to five years. Therefore, the need for warehousing would be preserved. The authors noted that they do not necessarily need to have it in-house. Consequently, fulfillment centers and warehouses would likely continue to be a significant component in the future logistics system. This research would like to stress how important the management of the effective optimization of e-commerce distribution center location is and how to achieve it. The success of Amazon in the US, Europe, and Alibaba in China has genuinely redefined consumer expectations. With the emergence of services like Amazon Prime, consumers now expect same-day delivery. The solution enabling this evolution has been a mix of manufacturing where the production costs are optimal, just-in-time shipping, highly automated fulfillment centers, and mobile connectivity growth. The proposed model results showed that the best location for a central location and storage center concerning the e-commerce environment, including minimum annual transport costs, is near Bristol in the United Kingdom. Eighty-six percent of the companies in the study plan to use on-demand warehousing in the next three to five years, and the solution enabling this evolution has been a combination of manufacturing where the production costs are optimal, just-in-time shipping, highly automated fulfillment centers, and, to a growing extent, mobile connectivity.


2011 ◽  
Vol 48-49 ◽  
pp. 547-550
Author(s):  
Cheng Lin Ma ◽  
Hai Jun Mao

Function area layout of underground distribution center is an important part of urban underground distribution center planning so that it would indirectly affect the building and development of underground distribution center and even the whole urban underground logistics system. Based on Automod simulation platform, the function area layout planning method was built in order to avoid underground operation invalidation because of the illogical function area layout. First by analyzing relative operation of underground distribution center, multi-objective 0-1 mixed integer programming model of function area layout was built based on two indexes of relativity and transit cost among function areas. Then the heuristic algorithm or exact algorithm was used to solve the mathematical model mathematical model and find out the layout scheme after quantifying the indicators. Finally the final layout was gained by simulation and optimization of Automod simulation platform. There was an example for proving the feasibility of the method. The results showed that the method was available to analyze the function area layout impact and it was very important for decision-making of building the underground distribution center.


2015 ◽  
Vol 743 ◽  
pp. 338-342
Author(s):  
Yong Liu ◽  
Jing Jie Sun ◽  
Xuan Wang

The article combines Fruit Fly optimization algorithm with Immune Optimization Algorithm into Fruit Fly-Immune algorithm to solve the multi-distribution center location problem with a NP-hard nature. Using MATLAB simulation technology and comparing to the simulation results of traditional Immune Optimization Algorithm shows that the use of Fruit Fly-Immune algorithm to solve multi-distribution center location problem can get better convergence results and weaken faster.


2021 ◽  
Vol 40 (4) ◽  
pp. 8493-8500
Author(s):  
Yanwei Du ◽  
Feng Chen ◽  
Xiaoyi Fan ◽  
Lei Zhang ◽  
Henggang Liang

With the increase of the number of loaded goods, the number of optional loading schemes will increase exponentially. It is a long time and low efficiency to determine the loading scheme with experience. Genetic algorithm is a search heuristic algorithm used to solve optimization in the field of computer science artificial intelligence. Genetic algorithm can effectively select the optimal loading scheme but unable to utilize weight and volume capacity of cargo and truck. In this paper, we propose hybrid Genetic and fuzzy logic based cargo-loading decision making model that focus on achieving maximum profit with maximum utilization of weight and volume capacity of cargo and truck. In this paper, first of all, the components of the problem of goods stowage in the distribution center are analyzed systematically, which lays the foundation for the reasonable classification of the problem of goods stowage and the establishment of the mathematical model of the problem of goods stowage. Secondly, the paper abstracts and defines the problem of goods loading in distribution center, establishes the mathematical model for the optimization of single car three-dimensional goods loading, and designs the genetic algorithm for solving the model. Finally, Matlab is used to solve the optimization model of cargo loading, and the good performance of the algorithm is verified by an example. From the performance evaluation analysis, proposed the hybrid system achieve better outcomes than the standard SA model, GA method, and TS strategy.


2016 ◽  
Vol 10 (10) ◽  
pp. 133
Author(s):  
Mohammad Ali Nasiri Khalili ◽  
Mostafa Kafaei Razavi ◽  
Morteza Kafaee Razavi

Items supplies planning of a logistic system is one of the major issue in operations research. In this article the aim is to determine how much of each item per month from each supplier logistics system requirements must be provided. To do this, a novel multi objective mixed integer programming mathematical model is offered for the first time. Since in logistics system, delivery on time is very important, the first objective is minimization of time in delivery on time costs (including lack and maintenance costs) and the cost of purchasing logistics system. The second objective function is minimization of the transportation supplier costs. Solving the mathematical model shows how to use the Multiple Objective Decision Making (MODM) can provide the ensuring policy and transportation logistics needed items. This model is solved with CPLEX and computational results show the effectiveness of the proposed model.


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