On the use of genetic programming to evolve priority rules for resource constrained project scheduling problems

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@Article{CHAND:2018:IS,

• author = "Shelvin Chand and Quang Huynh and Hemant Singh and Tapabrata Ray and Markus Wagner",
• title = "On the use of genetic programming to evolve priority rules for resource constrained project scheduling problems",
• journal = "Information Sciences",
• volume = "432",
• pages = "146--163",
• year = "2018",
• keywords = "genetic algorithms, genetic programming, Resource constrained project scheduling, Heuristic evolution, Evolutionary computation, Generation hyper-heuristics",
• ISSN = "0020-0255",
• DOI = "doi:10.1016/j.ins.2017.12.013",
• URL = "http://www.sciencedirect.com/science/article/pii/S0020025517311350",
• abstract = "Resource constrained project scheduling is critical in logistic and planning operations across a range of industries. Most businesses rely on priority rules to determine the order in which the activities required for the project should be executed. However, the design of such rules is non-trivial. Even with significant knowledge and experience, human experts are understandably limited in terms of the possibilities they can consider. This paper introduces a genetic programming based hyper-heuristic (GPHH) for producing efficient priority rules targeting the resource constrained project scheduling problem (RCPSP). For performance analysis of the proposed approach, a series of experiments are conducted on the standard PSPLib instances with up to 120 activities. The evolved priority rules are then compared against the existing state-of-the-art priority rules to demonstrate the efficacy of our approach. The experimental results indicate that our GPHH is capable of producing reusable priority rules which significantly out-perform the best human designed priority rules",

}

Genetic Programming entries for Shelvin Chand Quang Nhat Huynh Hemant Singh Tapabrata Ray Markus Wagner

Citations