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充分利用具体优化问题的模型空间结构或性质,往往可以减少搜索的不确定性,提高优化效率。多目的间歇生产调度形成的混合整数规划模型中只有0-1变量和连续变量,而且0-1变量和部分连续变量有对应关系。根据问题的特点将原模型分解为含有0-1变量的优化主问题和连续变量的子问题,并提出分解算法,降低了相应连续子规划的规模和复杂度。从计算复杂度的角度分析分解算法适用的问题情形,并用一个典型的批量生产调度问题进行分析实验,结果表明分解算法可以降低实际计算的复杂度,提高解的质量。
Making full use of the spatial structure or nature of the model of a specific optimization problem can often reduce the uncertainty of the search and improve the optimization efficiency. There are only 0-1 variables and continuous variables in the mixed integer programming model formed by multi-purpose batch production scheduling, and there is a corresponding relationship between 0-1 variables and some continuous variables. According to the characteristics of the problem, the original model is decomposed into sub-problems of optimization and continuous variables with 0-1 variables, and the decomposition algorithm is proposed to reduce the size and complexity of corresponding continuous sub-programs. From the point of view of computational complexity, this paper analyzes the applicable problems of decomposition algorithm and analyzes the experiment with a typical batch production scheduling problem. The results show that the decomposition algorithm can reduce the complexity of the actual calculation and improve the quality of the solution.