A multi-agent genetic algorithm for resource constrained project scheduling problems

Authors:
Xiaoxiao Yuan;Chuanfu Xiao;Xiyu Lv;Jing Liu
Affiliations:
School of Electronic Engineering, Xidian University, Xi'an, China;School of Electronic Engineering, Xidian University, Xi'an, China;School of Electronic Engineering, Xidian University, Xi'an, China;School of Electronic Engineering, Xidian University, Xi'an, China
Venue:
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Year:
2013

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Abstract

A multi-agent genetic algorithm is proposed to solve single-mode resource constrained project scheduling problems (MAGA-RCPSPs). In MAGA-RCPSPs, an agent represents a candidate solution to the RCPSP, and all agents live in a latticelike environment, with each agent fixed on a lattice point. In the experiments, benchmark problems Patterson and J30 are used. The results show that MAGA-RCPSPs has a good performance.