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中文摘要：
提出了一类具有丁件交货期和工装数量约束的平行机调度问题。以降低部件拖期惩罚总费用为目标，建立了该问题的数学模型．提出一种遗传与模拟退火相混合的算法来求解该类问题，即GASA算法。算法在初始种群的生成上，采取了随机生成和按启发式规则生成相结合的方法；并引入模拟退火算法作为变异算子，以提高种群的多样性。最后，通过实例仿真，验证了GASA算法的有效性，并与GA算法进行了对比，对比结果表明GASA更优越。
英文摘要：
An integrated problem was studied for parallel machines scheduling, in which the constraints of part delivery deadline and quantities of tooling were considered. To reduce tardiness penalty costs, a single model was build up to describe the whole problem. A genetic-simulated annealing algorithm was proposed to solve the problem, A new initialization method is proposed, which combines generation through heuristic rules with random generation. Finally, simulations reveal that the algorithm is eft~etive. And simulated annealing algorithm is adopted to be mutation operator. Comparing genetic-simulated annealing algorithm with genetic algorithm, results show out that the scheduling model and the algorithm are more effective and superior.
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