Evolutionary algorithms for the project scheduling problem: runtime analysis and improved design

Authors:
Leandro L. Minku;Dirk Sudholt;Xin Yao
Affiliations:
University of Birmingham, Birmingham, United Kingdom;University of Sheffield, Sheffield, United Kingdom;University of Birmingham, Birmingham, United Kingdom
Venue:
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Year:
2012

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Abstract

Even though genetic algorithms (GAs) have been used for solving the project scheduling problem (PSP), it is not well understood which problem characteristics make it difficult/easy for GAs. We present the first runtime analysis for the PSP, revealing what problem features can make PSP easy or hard. This allows to assess the performance of GAs and to make informed design choices. Our theory has inspired a new evolutionary design, including normalisation of employees' dedication for different tasks to eliminate the problem of exceeding their maximum dedication. Theoretical and empirical results show that our design is very effective in terms of hit rate and solution quality.