Agent-Based Dantzig-Wolfe Decomposition

Authors:
Johan Holmgren;Jan A. Persson;Paul Davidsson
Affiliations:
Department of Systems and Software Engineering, Blekinge Institute of Technology, Soft Center, Ronneby, Sweden 372 25;Department of Systems and Software Engineering, Blekinge Institute of Technology, Soft Center, Ronneby, Sweden 372 25;Department of Systems and Software Engineering, Blekinge Institute of Technology, Soft Center, Ronneby, Sweden 372 25
Venue:
KES-AMSTA '09 Proceedings of the Third KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications
Year:
2009

Citing 6
Cited 0

Branch-And-Price: Column Generation for Solving Huge Integer Programs

Operations Research
An adaptive solution to dynamic transport optimization

Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Distributed Lagrangean relaxation protocol for the generalized mutual assignment problem

AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Developing Multi-Agent Systems with JADE (Wiley Series in Agent Technology)

Developing Multi-Agent Systems with JADE (Wiley Series in Agent Technology)
Multi agent based simulation of transport chains

Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
On the Integration of Agent-Based and Mathematical Optimization Techniques

KES-AMSTA '07 Proceedings of the 1st KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present an agent-based approach to Dantzig-Wolfe column generation (a decomposition approach), which is applied to an integrated production, inventory, and distribution routing optimization problem. The decomposition model has been implemented in the Java programming language, using the Java Agent DEvelopment Framework (JADE) and the ILOG CPLEX mixed integer linear optimization problem solver. The model has been validated on a set of realistic scenarios and based on the results, we estimate the potential performance improvement which can be obtained by using a completely distributed implementation. We analyze the overhead, in terms of communication costs, that is imposed by an agent-based approach.