Genetic ArtificiaI Bee CoIony AIgorithm Faced with MuIti-objective and No-wait FIexibIe FIow Job-shop ScheduIing ProbIem
To solve no-wait and multi-objective flexible flow shop scheduling problem(NWMFJSP), proposes an optimization model, which takes fin-ished time of maximum, machine cost and total delayed time as the objectives. Then presents the distribution strategy of the grey mutual information relational adaptive value combined with the grey correlation and information entropy to evaluate feasible solution. Based on it, applies genetic artificial bee colony algorithm(GABC) to solve the problem, the algorithm, which presents the mutation based on key path, embeds artificial bee colony with the nutation, IPOX and MPX crossover to enhance ability to search optimal solution globally and raise convergence rate in late search. The validity and adaptability of the scheduling structure and algorithm are proved by a case of job-shop scheduling.
NETL
NSTL
万方数据
维普
