Multi-product Pricing Method Based on Improved Ant Colony Algorithm

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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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  -