Carryover for Actual Cost Based on Improved Genetic Algorithm

Abstract

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

Meng Qiunan, Lou Jian, Bai Xue. Carryover for Actual Cost Based on Improved Genetic Algorithm[J]. , 2016, 28(1): 179-190.

References

[1] 徐文娟,欧佩玉.ERP系统实施对我国企业会计人员角色和技能影响的实证研究[J]. 管理评论, 2013,25(2):149-160
[2] Ma B. Why Greed Works for Shortest Common Superstring Problem[J]. Theoretical Computer Science, 2009,410(51):5374-5381
[3] Kulp A., Hartman J. C. Optimal Tax Depreciation with Loss Carry-Forward and Backward Options[J]. European Journal of Operational Research, 2011,208(2):161-169
[4] Bunget O. C. Opinions on Allocation of Profit Carried Forward to Dividends[J]. Annals of the University of Oradea: Economic Science, 2009,18(3):817-821
[5] 杨家新.股票股利会计政策研究[J]. 会计研究, 2000,(3):48-52
[6] 许仁青.交易性金融资产后续计量年末结转的会计处理探析[J]. 合肥工业大学学报(社会科学版), 2013,27(3):23-25
[7] Murat A., Y?ar K., Bülent Y. Allocation of the General Production Costs to the Cost Centers by Linear Programming Method[J]. Journal of Accounting & Taxation Studies, 2014,7(1):53-65
[8] 孟欣苹.会计结转业务中的分析方法研究[J]. 中央财经大学学报, 2007,(4):87-91
[9] 吕春晓,宋合义.模拟法人之间内部结转价格的制订方法研讨[J]. 西安交通大学学报(社会科学版), 2001,21(1):35-38
[10] 申时凯,吴绍兵,申浩如等.计算最短公共超串的贪婪算法[J]. 计算机工程与设计, 2007,28(8):1757-1758
[11] Iliopoulos C., Rahman M. S., Vorá?ek M., et al. Finite Automata based Algorithms on Subsequences and Supersequences of Degenerate Strings[J]. Journal of Discrete Algorithms, 2010,8(2):117-130
[12] Mousavi S. R., Bahri F., Tabataba F. S. An Enhanced Beam Search Algorithm for the Shortest Common Supersequence Problem[J]. Engineering Applications of Artificial Intelligence, 2012,25(3):457-467
[13] Plociennik K. A Probabilistic PTAS for Shortest Common Superstring[J]. Theoretical Computer Science, 2014,522:44-53
[14] Castelli M., Beretta S., Vanneschi L. A Hybrid Genetic Algorithm for the Repetition Free Longest Common Subsequence Problem[J]. Operations Research Letters, 2013,41(6):644-649
[15] Laube U., Weinard M. Conditional Inequalities and the Shortest Common Superstring Problem[J]. International Journal of Foundations of Computer Science, 2005,16(6):1219-1230
[16] 雷伟军,程筱胜,戴宁等.基于改进遗传算法的多模型加工路径规划[J]. 机械工程学报, 2014,50(11):153-161