Automated design of priority rules for resource-constrained project scheduling problem using surrogate-assisted genetic programming
Luo, Jingyu Vanhoucke, Mario Coelho, José
Luo, Jingyu
Vanhoucke, Mario
Coelho, José
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Publication Type
Journal article with impact factor
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Supervisor
Publication Year
2023
Journal
Swarm and Evolutionary Computation
Book
Publication Volume
81
Publication Issue
August
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Abstract
In the past few years, the genetic programming approach (GP) has been successfully used by researchers to design priority rules for the resource-constrained project scheduling problem (RCPSP) thanks to its high generalization ability and superior performance. However, one of the main drawbacks of the GP is that the fitness evaluation in the training process often requires a very high computational effort. In order to reduce the runtime of the training process, this research proposed four different surrogate models for the RCPSP. The experiment results have verified the effectiveness and the performance of the proposed surrogate models. It is shown that they achieve similar performance as the original model with the same number of evaluations and better performance with the same runtime. We have also tested the performance of one of our surrogate models with seven different population sizes to show that the selected surrogate model achieves similar performance for each population size as the original model, even when the searching space is sufficiently explored. Furthermore, we have investigated the accuracy of our proposed surrogate models and the size of the rules they designed. The result reveals that all the proposed surrogate models have high accuracy, and sometimes the rules found by them have a smaller size compared with the original model.
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Keywords
Resource-Constrained Project Scheduling, Priority Rules, Genetic Programming, Surrogate Models