Abstract��For a kind of linear bi-level programming problems with interval coefficients in the upper level objective, a Genetic Algorithm (GA) was proposed by using a double fitness function evaluation technique, which was characterized by simultaneously obtaining the best optimal solution as well as the worst one in one run of the genetic algorithm. Firstly, individuals were encoded by using the vertices of the constraint region, and a double fitness was constructed by the upper and lower bounds of the upper level objective coefficients. Secondly, fitness functions were used to sort all individuals in populations. According to the order, the feasibility of individual was checked one by one until a feasible individual was found. Finally, the feasible individual was updated in executing algorithm. The simulation results on four computational examples show that the proposed algorithm is feasible and efficient.
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FAN Yangyang LI Hecheng. Genetic algorithm for solving linear bilevel programming with interval coefficients. Journal of Computer Applications, 2014, 34(1): 185-188.
2014, Vol. 34 
