Multiagent architecture (blueagents) with the dynamic pricing and maximum profit strategy in the TAC SCM

Authors:
David Han
Affiliations:
Research School of Information Sciences and Engineering, The Australian National University, Acton, Canberra, Australia
Venue:
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Year:
2005

Citing 8
Cited 0

Artificial Intelligence: A Modern Approach

Artificial Intelligence: A Modern Approach
A stochastic programming approach to scheduling in TAC SCM

EC '04 Proceedings of the 5th ACM conference on Electronic commerce
Redagent: winner of TAC SCM 2003

ACM SIGecom Exchanges
Value-driven procurement in the TAC supply chain game

ACM SIGecom Exchanges
TacTex-03: a supply chain management agent

ACM SIGecom Exchanges
PackaTAC: a conservative trading agent

ACM SIGecom Exchanges
Strategic trading agents via market modelling

ACM SIGecom Exchanges
Bidding for customer orders in TAC SCM

AAMAS'04 Proceedings of the 6th AAMAS international conference on Agent-Mediated Electronic Commerce: theories for and Engineering of Distributed Mechanisms and Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we propose a new agent architecture (BlueAgents) with the Dynamic Pricing and Maximum Profit Strategy (DPMPS). BlueAgents we design shows the flow of the trading as request for quotes, offer and order based on the time frame clearly and we describe the function modules that BlueAgents is composed of. One of the main foci of the decision making in a supply chain management for the trading agent competition (TAC SCM) is an optimization of the offer price under the uncertainty. Price is an important factor for maximizing benefit through the bidding process in competition with other agents. DPMPS is a benchmarking model to predict dynamically realistic optimal offer prices for bidding between an estimated offer price and regressed price of current market after estimating an optimized offer price for maximizing profit.