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[57400] Artykuł:

An Efficient Solution of the Resource Constrained Project Scheduling Problem Based on an Adaptation of the Developmental Genetic Programming

Czasopismo: Recent Advances In Computational Optimization: Results Of The Workshop On Computational Optimization Wco 2014   Tom: 610, Strony: 205-223
ISSN:  1860-949X
ISBN:  978-3-319-21133-6
Wydawca:  SPRINGER-VERLAG BERLIN, HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
Opublikowano: 2016
Seria wydawnicza:  Studies in Computational Intelligence
 
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Grzegorz Pawiński orcid logoWEAiIKatedra Systemów Informatycznych *5015.00  
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Grupa MNiSW:  Materiały z konferencji międzynarodowej (zarejestrowane w Web of Science)
Punkty MNiSW: 15
Klasyfikacja Web of Science: Proceedings Paper

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Keywords:

Minimisation  Project management  Scheduling  Search problems  Resource allocation  Evolutionary computations  Genetic algorithms  Developmental genetic programming 


Abstract:

An adaptation of the Developmental Genetic Programming (DGP) for solving an extension of the Resource-Constrained Project Scheduling Problem (RCPSP) is investigated in the paper. In DGP genotypes (the search space) and phenotypes (the solution space) are distinguished and a genotype-to-phenotype mapping (GPM) is used. Thus, genotypes are evolved without any restrictions and the whole search space is explored. RCPSP is a well-known NP-hard problem but in its original formulation it does not take into consideration initial resource workload and it minimises the makespan. We consider a variant of the problem when resources are only partially available and a deadline is given but it is the cost of the project that should be minimized. The goal of the evolution is to find a procedure constructing the best solution of the problem for which the cost of the project is minimal. The paper presents new evolution process for the DGP as well as a comparison with other genetic approaches. Experimental results showed that our approach gives significantly better results compared with other methods.


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