R Tavakkoli-Moghaddam - Department of Industrial Engineering, Faculty ofEngineering,University of Tehran
N Safaei - Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

This paper presents a comparison between a genetic algorithms (GA) based on queen bee and classical GA for scheduling flexible flow line problem with assuming blocking (FFLB). The proposed heuristics are used to solve a modified version of a mixed-integer mode of the FFLB. The flexible flow line consists of several processing stages in series separated by finite intermediate buffers, in which each stage has one or more identical parallel processors. The objective is to determine a production schedule for all products so as to complete the products in a minimum time (makespan). This paper also uses a novel crossover operator type inspired by the sexual intercourses of honey bees. The method selects a specific chromosome in present population as queen bee with highest fitness. While the selected queen bee is one parent of crossover, all the remaining chromosomes have the chance to be next parent for crossover in each generation once. The model of FFLB is solved by the classical GA (CGA) and queen-bee GA (QGA) and obtained results are compared together. To verify the efficiency of both CGA and QGA, we use a lower bound obtained from the Lingo 8. The results show that the convergence of QGA is faster rather than CGA in same conditions.

Flexible flow line, Processor Blocking, Queen bee Genetic algorithms