Soft Computing

, Volume 22, Issue 3, pp 845–859 | Cite as

Heuristic routing algorithm toward scalable distributed generalized assignment problem

Methodologies and Application
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Abstract

Distributed generalized assignment problem (D-GAP) is very popular in scalable multi-agent systems. However, existing algorithms are either not effective or efficient in large-scale or highly dynamic domains owing to limited communications and computational resources. In this paper, we present a novel approach named intelligent routing algorithm (IRA) to address this issue. In IRA, in order to reduce communication load, a decentralized model for agents is proposed to jointly search for optimized solutions. Moreover, due to the complexity of distributed generalized assignment problem (D-GAP) in a massive multi-agent system where agents cannot perform optimal search based on their local views, we propose a heuristic algorithm that can find an approximate optimized solution. By inferring knowledge from their previous communicated searches, agents are able to predict how to deploy future similar searches more efficiently. If an agent can solve some parts of D-GAP well, similar searches will be sent to it. By taking advantage of the accumulation effect to agents’ local knowledge, agents can independently make simple decisions with highly reliable performance and limited communication overheads. The simulation and the experimental results demonstrate the feasibility and efficiency of our algorithm.

Keywords

Multi-agent system D-GAP Heuristic routing algorithm 

Notes

Acknowledgments

This study was funded by NSFC 61370151 and 61202211, National Science and Technology Major Project of China 2015ZX03003012, Central University Basic Research Funds Foundation of China ZYGX2014J055 and the Science and Technology on Electronic Information Control Laboratory Project.

Compliance with ethical standards

Conflicts of interest

The authors declare that they have no conflict of interest

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.School of Computer Science and EngineeringUniversity of Electronic Science and Technology of ChinaChengduChina

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