Title :
The virus evolutionary genetic algorithm for non- full loaded vehicle scheduling problem with fuzzy time window
Author :
Bingyuan Lu ; Bayi Cheng
Author_Institution :
Sch. of Econ. & Manage., Nanjing Inst. of Technol., Nanjing, China
Abstract :
For the fuzzy time phenomenon caused by factors such as traffic and roads in distribution process, based on trapezoidal fuzzy number, this article gives one kind of vehicle scheduling problem model with fuzzy time window. In the problem solution aspect, this article, on the foundation of carrying on the genetic operation to the host chromosomes, introduces virus infection operation to infect the host chromosomes and combines dynamically the host chromosomes´ global evolution with the virus chromosomes´ local evolution to solve the problem of the precocious and the slow convergence rate existing in traditional genetic algorithm. The simulation experiment indicates that this algorithm has feasibility and validity.
Keywords :
fuzzy set theory; genetic algorithms; logistics; scheduling; fuzzy time window; host chromosomes global evolution; nonfull loaded vehicle scheduling problem; trapezoidal fuzzy number; virus chromosomes local evolution; virus evolutionary genetic algorithm; Biological cells; Encoding; Genetic algorithms; Genetics; Scheduling; Search problems; Vehicles; fuzzy time window; genetic algorithm; vehicle scheduling problem; virus mechanism;
Conference_Titel :
Natural Computation (ICNC), 2011 Seventh International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9950-2
DOI :
10.1109/ICNC.2011.6022047