An Improved Bat Algorithm and its Application in the Logistics Distribution Center Location Problem

2013 ◽  
Vol 404 ◽  
pp. 738-743
Author(s):  
Yue Guang Li
Keyword(s):  
Mathematical Model ◽  
Location Problem ◽  
Time Window ◽  
Influence Factors ◽  
Bat Algorithm ◽  
Distribution Center ◽  
Center Problem ◽  
Logistics Distribution ◽  
Distribution Logistics ◽  
Selection Operator

In this paper, according to the characteristics and influence factors of the distribution logistics and distribution center problem, a mathematical model of the distribution center of the LRTWP (Location and Routing with Time Window Problem) was established. An improved bat algorithm was used to solve the model, the parameter and selection operator in the algorithm is set reasonably. Simulations and results indicate that the improved bat algorithm has better feasibility and validity for solving the LRTWP.

An Improved Simulated Annealing Algorithm and its Application in the Logistics Distribution Center Location Problem

2013 ◽  
Vol 389 ◽  
pp. 990-994 ◽  
Author(s):  
Yue Guang Li
Keyword(s):  
Simulated Annealing ◽  
Location Problem ◽  
Simulated Annealing Algorithm ◽  
Time Window ◽  
Influence Factors ◽  
Distribution Center ◽  
Logistics Distribution ◽  
Distribution Logistics ◽  
Annealing Algorithm ◽  
Selection Operator

In this paper, according to the characteristics and influence factors of the distribution logistics and distribution center problem, a mathematical model of the distribution center of the LRTWP (Location and Routing with Time Window Problem) was established. An improved simulated annealing algorithm was used to solve the model, the parameter and selection operator in the algorithm is setted reasonably. Simulations and results indicate that the improved simulated annealing algorithm has better feasibility and validity for solving the LRTWP.

scholarly journals A Hybridization of Cuckoo Search and Differential Evolution for the Logistics Distribution Center Location Problem

2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Rui Chi ◽  
Yixin Su ◽  
Zhijian Qu ◽  
Xuexin Chi
Keyword(s):  
Differential Evolution ◽  
Optimization Algorithm ◽  
Location Problem ◽  
Cuckoo Search ◽  
Distribution Center ◽  
Metaheuristic Algorithms ◽  
Logistics Distribution ◽  
Center Location ◽  
Mutation Operation ◽  
Distribution Center Location

The location selection of logistics distribution centers is a crucial issue in the modern urban logistics system. In order to achieve a more reasonable solution, an effective optimization algorithm is indispensable. In this paper, a new hybrid optimization algorithm named cuckoo search-differential evolution (CSDE) is proposed for logistics distribution center location problem. Differential evolution (DE) is incorporated into cuckoo search (CS) to improve the local searching ability of the algorithm. The CSDE evolves with a coevolutionary mechanism, which combines the Lévy flight of CS with the mutation operation of DE to generate solutions. In addition, the mutation operation of DE is modified dynamically. The mutation operation of DE varies under different searching stages. The proposed CSDE algorithm is tested on 10 benchmarking functions and applied in solving a logistics distribution center location problem. The performance of the CSDE is compared with several metaheuristic algorithms via the best solution, mean solution, and convergence speed. Experimental results show that CSDE performs better than or equal to CS, ICS, and some other metaheuristic algorithms, which reveals that the proposed CSDE is an effective and competitive algorithm for solving the logistics distribution center location problem.

A Task Conflict Detection Model of Logistics Distribution

2012 ◽  
Vol 452-453 ◽  
pp. 736-740
Author(s):  
Qing Kui Cao ◽  
Qian Zhang
Keyword(s):  
Time Window ◽  
Time Windows ◽  
Distribution Center ◽  
Task Conflict ◽  
Scheduling Problem ◽  
Temporal Constraint ◽  
Logistics Distribution ◽  
Detection Model ◽  
Constraint Network ◽  
Multiple Tasks

Based on the time window in the vehicle scheduling problem(VSP), we propose the concept of time windows of delivery tasks(TWDT) in the distribution center, and describe the TWDT in a kind of three-tuple. Transferring time windows constraint of multiple tasks to a simple temporal constraint network, we simplify the problem of checking the time constraint of multiple tasks to the problem of checking the temporal constraint network’s consistency. According to the characteristic of delivery task and simple temporal constraint network, we proposed the model of time window conflict checking of delivery task.

Optimized Vehicle Scheduling Algorithm of Distribution Center

2013 ◽  
Vol 340 ◽  
pp. 581-586
Author(s):  
Zhu Wang
Keyword(s):  
Mathematical Model ◽  
Scheduling Algorithm ◽  
Time Windows ◽  
Distribution Center ◽  
Vehicle Scheduling ◽  
Scheduling Problem ◽  
Research Results ◽  
Logistics Distribution ◽  
The Mathematical Model

This thesis goes deep into the vehicle scheduling problem (VSP), which is the key problem for the distribution center.This paper analyzes and optimizes the mathematical model of vehicle scheduling problem. The problem of dynamic vehicle scheduling with time windows is described in great details in the thesis, which also gives an arithmetic solution aiming at the scheduling problem.Finally, based on the research results and under the background of logistics distribution enterprises, the vehicle scheduling algorithm is exposed to experiment.

The Research and Application on Location of Distribution Center Based on Grey Theory and AHP

2014 ◽  
Vol 1006-1007 ◽  
pp. 464-467
Author(s):  
Hai Dong ◽  
Jian Hua Yan ◽  
Heng Bao Xin
Keyword(s):  
Location Problem ◽  
Distribution Center ◽  
Grey Theory ◽  
Logistics Distribution

Location of logistics distribution center is affected by many factors, so choosing an appropriate method to evaluate is extremely important. Location problem of logistics distribution center by using the method of AHP and grey theory is analyzed and evaluated, and the corresponding model is put forward. Finally, the examples show that the model can effectively deal with the location problem of logistics distribution center.

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