id: 06001105
dt: j
an: 1240.90136
au: Bai, Junjie; Wang, Ningsheng; Tang, Dunbing
ti: An improved PSO algorithm for multi-objective optimization flexible job
    shop scheduling problems.
so: J. Nanjing Univ. Aeronaut. Astronaut. 42, No. 4, 447-453 (2010).
py: 2010
pu: Nanjing University of Aeronautics \& Astronautics, Nanjing
la: ZH
cc: 90B35 90C59 90C29
ut: flexible job shop scheduling; particle swarm optimization algorithm;
    multi-objective optimization; preference information
ci: 
li: 
ab: Summary: In order to solve the multi-objective flexible job shop scheduling
    problems with a large dimensional searching space, a preference based
    multi-objective particle swarm optimization algorithm is proposed. The
    preference information of the decision maker is incorporated into an
    algorithm to lead the searching direction. So that the searching space
    is compressed and the efficiency of the algorithm is improved.
    Moreover, just a few trade-off solutions located in the preferred area
    are obtained in a single run, and the hard work of choosing a
    satisfying solution from numerous non-inferior solutions is eliminated.
    In the algorithm, a new expression method for preference information is
    proposed based on an importance relationship among objectives and the
    value range of objectives or objective weights. With the method, the
    preference of the decision maker can easily be specified, and the range
    of searching area can be adjusted according to the requirements of the
    decision maker. In view of the characteristics of preference
    information, a new preference information handling method for
    simulating the “vote" of human society is proposed. The method is
    intuitive, simple and easy to be used. Finally, the performance of the
    algorithm is evaluated by simulations. Results demonstrate the
    feasibility and efficiency of the proposed algorithm.
rv: