Genetic algorithm approach to constructing flexible production schedules

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1, A method for solving large-scale scheduling problems based on search space decomposition.When the problem includes many variables, the individual in GA is represented in terms of plural chromosomes. Consequently the search space is decomposed and the optimal solution is obtained efficiently by applying heuristics to the search in the decomposed space.2, A method for constructing GA to treat the problem constraints flexiblyThe individual description is defined and the genetic operators are designed so as to obtain a feasible solution for the problem with complicated constraints.3, A method of rescheduling by using GAWhen the problem includes constraint variations, the initial population is constructed so as to solve a rescheduling problem easily.4, An optimal schedule for large-scale job shop processes with various constraintsThe individual description and introduction of heuristics are proposed for solving large-scale job shop scheduling problems with additional constraints.5, An optimal schedule for flow shop processes with parallel machinesFor treating complicated flow shop scheduling problems, GA is designed by combining some dispatching rules with the conventional genetic operators.