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A modified genetic algorithm for precedence constrained operation sequencing problem in process planning

机译:工艺计划中优先约束操作排序问题的改进遗传算法

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Precedence constrained operation sequencing problem (PCOSP) is concerned with selection of feasible and efficient operation sequence with minimal machining cost in process planning. Traditional genetic algorithm (GA) generates solution sequence by using randomly selection and insertion of operations, which will break the precedence constraints between operations. The additional fixing approaches for the infeasible solutions will result in low efficiency. Some modified GAs could generate feasible solutions but have premature convergence problem when facing complicated precedence constraints. To overcome the shortcomings, this paper proposed a modified GA that use an edge selection based chromosome encoding approach to make sure all the precedence constraints are met in every step. The experiment illustrates that the proposed GA has superiority in finding optimal or near optimal solution.
机译:优先约束操作顺序问题(PCOSP)与在过程规划中选择可行且高效的操作顺序以及最小的加工成本有关。传统遗传算法(GA)通过随机选择和插入操作来生成求解序列,这将打破操作之间的优先约束。对于不可行的解决方案,附加的固定方法将导致效率低下。一些经过改进的遗传算法可能会产生可行的解决方案,但是在面对复杂的优先约束时会出现过早收敛的问题。为了克服这些缺点,本文提出了一种改进的遗传算法,该遗传算法使用基于边缘选择的染色体编码方法来确保在每个步骤中都满足所有优先级约束。实验表明,提出的遗传算法在寻找最优解或接近最优解方面具有优势。

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