管理评论

›› 2016, Vol. 28 ›› Issue (1): 179-190.

• 会计与财务管理 • 上一篇    下一篇

基于改进遗传算法的实际成本结转方法

蒙秋男, 娄剑, 白雪   

  1. 大连理工大学管理与经济学部, 大连 116024
  • 收稿日期:2013-07-04 出版日期:2016-01-30 发布日期:2016-02-01
  • 作者简介:蒙秋男,大连理工大学管理与经济学部副教授,硕士生导师,博士;娄剑,大连理工大学管理与经济学部硕士研究生;白雪,大连理工大学管理与经济学部硕士研究生。
  • 基金资助:

    国家自然科学基金项目(71172137;61034003);国家科技支撑计划项目(2015BAF08B02)。

Carryover for Actual Cost Based on Improved Genetic Algorithm

Meng Qiunan, Lou Jian, Bai Xue   

  1. Faculty of Management and Economics, Dalian University of Technology, Dalian 116024
  • Received:2013-07-04 Online:2016-01-30 Published:2016-02-01

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摘要：

为了解决多步骤复杂生产过程中实际成本无法根据实物流转过程准确结转的问题,以基于产品、批次的实际成本结转为研究对象,构建成本结转数学模型。设计一种改进的遗传算法对模型进行求解:提出了顺序约束下的两层分片段染色体编码、解码方法,省去了复杂的解码修复操作;构造了基于基因小片段的多次交叉算子和分层多点变异算子以及选择策略,包括最优个体保留、个体选择次数限制以及种群扰动策略,克服了算法早熟收敛。通过算例的仿真实验和对比分析,表明改进遗传算法是求解成本中心结转优化顺序的有效方法,该算法与基本遗传算法相比收敛速度更快、结果更优。最后以某企业的实际成本数据为例,将上述成本结转方法与企业目前采用的结转方法进行对比,表明该方法在提高成本核算的准确性以及缩短成本核算时间上具有较好的效果。

关键词: 成本核算, 成本结转, 成本中心串, 改进遗传算法

Abstract:

To solve the problem of actual cost carryover with the product circulations accurately in complex production processes, the cost carryover mathematical model which takes the product and batch as main research objects is built up. The improved Genetic Algorithm (GA) is designed to solve the model. The chromosome encoding and decoding with two layers of segments under the constraint of sequences are presented to realize valid chromosomes in the whole evolution process of GA and omit the complex operations of decoding and repairing. The multi-point crossover and mutation with gene fragments are provided. The population perturbation strategy including optimum retention, roulette wheel selection limits on the number of individual and population disturbance is proposed to overcome the premature convergence. Compared with basic Genetic Algorithm, the improved GA is better in accuracy and efficiency. Finally, an illustrative example is given to testify this above method with the carryover method used in the enterprise; the results show that the improved GA has better effectiveness in improving costing accuracy and decreasing the time of accounting.

Key words: accounting, carryover, cost center string, improved Genetic Algorithm