Proceedings of 3rd International Symposium on Social Science (ISSS 2017)

Multi-product Pricing Method Based on Improved Ant Colony Algorithm

Authors
Jing Xu, Qiunan Meng
Corresponding Author
Jing Xu
Available Online May 2017.
DOI
10.2991/isss-17.2017.82How to use a DOI?
Keywords
Multi-product pricing, stochastic demand, product quality, improved ant colony algorithm
Abstract

Integrating with the due-date and quality demand of customers, a dynamic pricing model with stochastic demand and capacity constraint which aimed to maximize total profit and average quality was established for the multi-product pricing problem with random parameter. A weight space ant colony optimization algorithm (WSACO) was proposed, which allowed ant's search direction to adjust dynamically according to the current Pareto solutions, thus improving the global searching capability efficiently. Compared to the Bi-criterion Ant (BIANT) algorithm, it obtains higher solving accuracy, the results also show that the WSACO algorithm presents better performance in improving profit and product quality and provides method support for multi-product pricing decisions of enterprises.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of 3rd International Symposium on Social Science (ISSS 2017)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
May 2017
ISBN
10.2991/isss-17.2017.82
ISSN
2352-5398
DOI
10.2991/isss-17.2017.82How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Jing Xu
AU  - Qiunan Meng
PY  - 2017/05
DA  - 2017/05
TI  - Multi-product Pricing Method Based on Improved Ant Colony Algorithm
BT  - Proceedings of 3rd International Symposium on Social Science (ISSS 2017)
PB  - Atlantis Press
SP  - 364
EP  - 370
SN  - 2352-5398
UR  - https://doi.org/10.2991/isss-17.2017.82
DO  - 10.2991/isss-17.2017.82
ID  - Xu2017/05
ER  -