@article {IOPORT.05781313,
    author       = {Brudaru, Octav and Valmar, Brent and Popovici, D.},
    title        = {Hybrid genetic algorithm for assembly line balancing with fuzzy times and parallel workstations.},
    year         = {2008},
    journal      = {Buletinul Institutului Politehnic din Ia\c{s}i. Sec\c{t}ia Automatic\u{a} \c{s}i Calculatoare},
    volume       = {54(58)},
    number       = {2},
    issn         = {1220-2169},
    pages        = {71-50},
    publisher    = {Universitatea Tehnic\u{a} "Gheorge Asachi" Ia\c{s}i; Editura Politehnium},
    abstract     = {Summary: This paper deals with the design of balanced assembly lines with parallel workstations in the case when the execution times are real sampled fuzzy numbers. The need for parallel workstations appears whenever the assembly process contains some tasks whose processing times are longer than the cycle time. The variant when the execution times are fuzzy number was considered as a better compromise between the reality modelling and the efficiency of the solving techniques. In order to solve this problem, it is proposed an efficient greedy algorithm that constructs an assembly structure containing both serial and parallel workstations for a prescribed confidence threshold. An optimal detecting criterion allows the obtaining of a simple relationship between the solution given by the algorithm and an easily calculated lower bound of the number of serial and parallel workstations. The greedy algorithm is grafted on a genetic algorithm resulting a powerful tool for solving this problem. The performance of the hybrid genetic algorithm related to the efficiency of defuzzyfication rules, the optimality of the number of workstations, the absolute and relative deviation from the optimal value, are experimentally analyzed.},
    identifier   = {05781313},
}