An Improved Particle Swarm Optimization for the Automobile Spare Part Warehouse Location Problem

Joint Authors

Yaobao, Zhen
Ping, Hu
Shu, Yang

Source

Mathematical Problems in Engineering

Issue

Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-6, 6 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2013-11-28

Country of Publication

Egypt

No. of Pages

6

Main Subjects

Civil Engineering

Abstract EN

This paper deals with a real-life warehouse location problem, which is an automobile spare part warehouse location problem.

Since the automobile spare part warehouse location problem is a very complex problem, particle swarm optimization is used and some improved strategies are proposed to improve the performance of this algorithm.

At last, the computational results of the benchmark problems about warehouse location problems are used to examine the effectiveness of particle swarm optimization.

Then the results of the real-life automobile spare part warehouse location problem also indicate that the improved particle swarm optimization is a feasible method to solve the warehouse location problem.

American Psychological Association (APA)

Yaobao, Zhen& Ping, Hu& Shu, Yang. 2013. An Improved Particle Swarm Optimization for the Automobile Spare Part Warehouse Location Problem. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-1032119

Modern Language Association (MLA)

Yaobao, Zhen…[et al.]. An Improved Particle Swarm Optimization for the Automobile Spare Part Warehouse Location Problem. Mathematical Problems in Engineering No. 2013 (2013), pp.1-6.
https://search.emarefa.net/detail/BIM-1032119

American Medical Association (AMA)

Yaobao, Zhen& Ping, Hu& Shu, Yang. An Improved Particle Swarm Optimization for the Automobile Spare Part Warehouse Location Problem. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-1032119

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1032119