Present paper aims to optimize the order batching problem expressed in mathematical language. There, the design and solving steps of order batching problem are based on genetic algorithm. The genetic algorithm in solving process variation method is used to realize the optimization of the model in order to enhance the efficiency of batch picking which increases customer’s satisfaction. Our result explored herein lies that the single order picking equipment limited factor has been extended to multiple sorting equipment in distribution center selection process.
| Published in | American Journal of Biological and Environmental Statistics (Volume 1, Issue 2) |
| DOI | 10.11648/j.ajbes.20150102.11 |
| Page(s) | 46-50 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2016. Published by Science Publishing Group |
Manual Order Picking System, Order Batching, Genetic Algorithm
| [1] | Gibson D.R. and Sharp G.P., Order batching procedures, European Journal of Operational Research, Vol. 58(l), pp. 57-67, 2005. |
| [2] | Le-Due and De Koste, Travel distance estimation and storage zone optimization in a 2-bloek class-based storage strategy warehouse, Interactional Journal of Production Research, Vol. 43(17), pp. 3561-3581, 2004. |
| [3] | Maurya V.N. and Garg Madhu Bala, An alternative approach for determining an optimum assignment schedule in management systems, Acta Ciencia Indica Mathematics, Vol. 32 M, No. 3, pp. 1017-1022, 2006 (Citation No. 015880, Indian Science Abstract, Vol. 43, No. 16, 2007), ISSN: 0970-0455. |
| [4] | Maurya V.N., Bathla Rajender Kumar, Maurya Avadhesh Kumar, Arora Diwinder Kaur and Gautam R.A., An alternate efficient sorting algorithm applicable for classification of versatile data, International Journal of Mathematical Modeling and Applied Computing, Academic & Scientific Publishing, New York, USA, Vol.1(1), pp. 1-10, 2013, ISSN: 2332-3744. |
| [5] | Maurya V.N., Misra R.B., and Maurya A.K., Mathematical modeling and optimization of memorization process to enhance learning using differential equations approach, Journal of Cell Science & Theory (JCEST),USA, ISSN 2157-7013, Vol. 4(4), pp 155, 2013. |
| [6] | Maurya V.N., Misra R.B., Jaggi Chandra K., Maurya A.K. and Arora D.K., Progressive review and analytical approach for optimal solution of stochastic transportation problems (STP) involving multi choice cost, American Journal of Modeling and Optimization, Science & Education Publishing, USA, Vol. 2(3), pp. 77-83, 2014, ISSN (Print) 2333-1143, ISSN (Online) 2333-1267. |
| [7] | Maurya V.N., Reddy Narendra, Maurya Avadhesh Kumar, Datt Nikleshwar, Optimization perspectives and effectiveness of gender in organizational leadership: Scenario of employees satisfaction and organizational goals, IEC University Journal of Engineering, Management and Sciences, India, Vol. 1(1), pp. 15-29, 2014. |
| [8] | Maurya Vishwa Nath, Misra Ram Bilas, Jaggi Chandra K., Vashist Swammy, Maurya Avadhesh K., and Shukla Kamlesh Kumar, Two dimensional multiobjective programming problem using graphical approach, American Journal of Biological and Environmental Statistics, Science Publishing Group, USA, Vol. 2(1), 2016. |
| [9] | Pratik J. Parikh and Russell D. Meller, Selecting between batch and zone order picking strategies in a distribution center, Transportation Research Part E, Vol.44, pp. 696-719, 2008. |
| [10] | Roodbergen K.J. and De Koster R., Routing order pickers in a ware house with a middle aisle. European Journal of Operational Research, Vol.133, pp.32-43, 2001. |
| [11] | Tho Le-Duc, Design and control of efficient order picking processes Rotterdam: Erasmus University Rotterdam, 2005. |
APA Style
Vishwa Nath Maurya. (2016). Realistic Batch Picking Route Optimization Model Using Genetic Algorithms. American Journal of Biological and Environmental Statistics, 1(2), 46-50. https://doi.org/10.11648/j.ajbes.20150102.11
ACS Style
Vishwa Nath Maurya. Realistic Batch Picking Route Optimization Model Using Genetic Algorithms. Am. J. Biol. Environ. Stat. 2016, 1(2), 46-50. doi: 10.11648/j.ajbes.20150102.11
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Download@article{10.11648/j.ajbes.20150102.11,
author = {Vishwa Nath Maurya},
title = {Realistic Batch Picking Route Optimization Model Using Genetic Algorithms},
journal = {American Journal of Biological and Environmental Statistics},
volume = {1},
number = {2},
pages = {46-50},
doi = {10.11648/j.ajbes.20150102.11},
url = {https://doi.org/10.11648/j.ajbes.20150102.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajbes.20150102.11},
abstract = {Present paper aims to optimize the order batching problem expressed in mathematical language. There, the design and solving steps of order batching problem are based on genetic algorithm. The genetic algorithm in solving process variation method is used to realize the optimization of the model in order to enhance the efficiency of batch picking which increases customer’s satisfaction. Our result explored herein lies that the single order picking equipment limited factor has been extended to multiple sorting equipment in distribution center selection process.},
year = {2016}
}
TY - JOUR T1 - Realistic Batch Picking Route Optimization Model Using Genetic Algorithms AU - Vishwa Nath Maurya Y1 - 2016/06/16 PY - 2016 N1 - https://doi.org/10.11648/j.ajbes.20150102.11 DO - 10.11648/j.ajbes.20150102.11 T2 - American Journal of Biological and Environmental Statistics JF - American Journal of Biological and Environmental Statistics JO - American Journal of Biological and Environmental Statistics SP - 46 EP - 50 PB - Science Publishing Group SN - 2471-979X UR - https://doi.org/10.11648/j.ajbes.20150102.11 AB - Present paper aims to optimize the order batching problem expressed in mathematical language. There, the design and solving steps of order batching problem are based on genetic algorithm. The genetic algorithm in solving process variation method is used to realize the optimization of the model in order to enhance the efficiency of batch picking which increases customer’s satisfaction. Our result explored herein lies that the single order picking equipment limited factor has been extended to multiple sorting equipment in distribution center selection process. VL - 1 IS - 2 ER -
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