Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization
Proceedings of the 5th International Conference on Genetic Algorithms
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The scheduling of activities to distribute oil derivate products through a pipe network is a complex combinatorial problem that presents a hard computational solution. This problem could be decomposed on three sub problems according to the key elements of scheduling: assignment of resources, sequencing of activities, and determination of resource timing utilization by these activities. This work develops a model to the sequencing sub-problem. The main objective is to develop a multi-objective genetic algorithm to order oil derivate products batches input into the network. From the operational practice, the batches sequencing has great influence on the final scheduling result. The MOGA model provides a set of solutions that means different options of pipeline operations, in a small computational time. This work contributes to the development of a tool to aid the specialist to solve the batch sequencing problem, which reflects in a more efficient use of the pipeline network.