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Multiagent Genetic Optimization to Solve the Project Scheduling Problem

Authors:
Konstantin Aksyonov
Anna Antonova

Keywords: Project scheduling; genetic algorithms; simulation; subcontract work optimisation.

Abstract:
This paper considers a project scheduling problem belonging to a class of multiobjective problems of complex systems control, whose decision search time grows exponentially depending on the problem dimension. In this paper, a survey of a modified genetic algorithm application to the project scheduling problem is presented. We propose a multiagent genetic optimisation method based on evolutionary and multiagent modelling by implementing different decision searching strategies, including a simulation module. The multiagent simulation module is intended to evaluate chromosome fitness functions and describe the dynamic nature of own and subcontracted resources allocation. The proposed multiagent genetic optimisation method, the MS Project resource reallocation method, and a heuristic simulation method have been compared whilst addressing a real-world scheduling problem. The comparison has shown: firstly, the unsuitability of the MS Project planning method to solve the formulated problem; and secondly, both the advantage of the multiagent genetic optimisation method in terms of economic effect and disadvantage in terms of performance. Some techniques to reduce the impact of the method’s disadvantage are proposed in the conclusion, as well as the aims of future work.

Pages: 237 to 243

Copyright: Copyright (c) IARIA, 2013

Publication date: July 21, 2013

Published in: conference

ISSN: 2308-4529

ISBN: 978-1-61208-283-7

Location: Nice, France

Dates: from July 21, 2013 to July 26, 2013