Optimizing earthmoving operations using object-oriented simulation
Proceedings of the 32nd conference on Winter simulation
An Introduction to Genetic Algorithms for Scientists and Engineers
An Introduction to Genetic Algorithms for Scientists and Engineers
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
On the use of fuzzy clustering in construction simulation
Proceedings of the 33nd conference on Winter simulation
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This paper presents an application of simulation optimization in construction utilizing genetic algorithms. The paper focuses on the use of genetic algorithms (GAs) as a tool for optimizing the total cost of earthmoving operations accounting for available equipment models to contractors and their corresponding quantities. The developed genetic algorithm has a powerful computational utility that increases its efficiency. The fitness of generated chromosomes is calculated utilizing a simulation engine dedicated for earthmoving operations which is dynamically linked to the developed genetic algorithm. The impact of the algorithm's control parameters on its conversion is also examined. A numerical example is presented to illustrate the capabilities of the developed algorithm in selecting near-optimum fleet configurations.