How to cite this paper
Agarwal, R. (2017). Decision making with association rule mining and clustering in supply chains.International Journal of Data and Network Science, 1(1), 11-18.
Refrences
Anand, S. S., Hughes, J. G., Bell, D. A., & Patrick, A. R. (1997).Tackling the cross- sales problem using data mining. Proceedings of the 2nd Pacific-Asia Conference on Knowledge Discovery & Data Mining (pp. 331-343). Hongkong.
Brijs, T., Swinnen, G., Vanhoof, K., & Wets, G. (1999).Using association rules for product assortment decisions: A case study. Proceedings of the 5th ACM SIGKDD International Conference on Knowledge discovery & data mining (pp. 254-260). New York, USA.
Brijs, T., Swinnen, G., Vanhoof, K., & Wets, G. (2000). A data mining framework for optimal product selection in retail supermarket data: The generalized PROFSET model. Proceedings of the 6th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (pp. 300-304). New York, USA.
Bala, P. K. (2008). Identification of purchase dependencies in retail sale. International Journal of Strategic Management, 8(2), 75–83.
Bala, P. K., Sural, S., & Banerjee, R. N. (2010). Association rule for purchase dependence in multi-item inventory. Production Planning and Control, 21(3), 274–285.
Bala, P. K. (2012). An inventory replenishment model under purchase dependency in retail sale. International Journal of Computer Applications, 37(10), 43–48.
Chase, R. B., Aquilano, N. J., & Jacobs, F. R. (1998). Production & operations management manufacturing & services (8thed.). McGraw-Hill companies.
Cheng, Y. (2005). Genetic algorithm for item selection with cross-selling considerations. Proceedings of the 4th International Conference on Machine Learning and Cybernetics. China. (pp. 3293-3298).
Cohen, M. A., & Ernst, R. (1988). Multi-item classification and generic inventory stock control Policies. Production & Inventory Management Journal, 29(3), 6–8.
Flores, B. E., & Whybark, D. C. (1987). Implementing multiple criteria ABC analysis. Journal of Operations Management, 7(1 & 2), 79–85.
Kaku, I. (2004). A data mining framework for classification of inventories. Proceedings of the 5thAsia Pacific Industrial Engineering & Management Systems (pp. 450-455). Japan.
Kaku, I., & Xiao, Y. (2008). A new algorithm of inventory classification based on the association rules. International Journal of Services Sciences, 1(2), 148–163.
Kleinberg, J. (1998). Authoritative sources in a hyperlinked environment. Proceedings of the 9th ACM-SIAM Symposium on Discrete Algorithms(pp. 668-677).San Francisco, California, USA.
Lenard, J. D., & Roy, B. (1995). Multi-item inventory control: A multicriteria view. European Journal of Operational Research, 87(3), 685–692.
Mittal, M., Pareek, S., & Agarwal, R. (2014). Efficient ordering policy for imperfect quality items using association rule mining. In Encyclopedia of information science and technology (3rd ed., pp. 773–786). United states: Information Science publishing.
Mittal, M., Pareek, S., & Agarwal, R. (2015a). Loss profit estimation using association rule mining with clustering. Management Science Letters, 5(2), 167–174.
Mittal, M., Pareek, S., & Agarwal, R. (2015b). Ordering policy using temporal association rule mining. International Journal of Data Science, 1(2), 157-171.
Mittal, M., Pareek, S., & Agarwal, R. (2016). Loss profit estimation using temporal association rule mining. International Journal of Business Analytics, 3(1), 45-57.
Ng, W. L. (2007). A simple classifier for multiple criteria ABC analysis. European Journal of Operational Research, 177(1), 344-353.
Ozan, C., & Mustafa, S.C. (2008). A web-based decision support system for multi-criteria inventory classification using fuzzy AHP methodology. Expert Systems with Applications, 35(3), 1367–1378.
Ramanathan, R. (2006). ABC inventory classification with multiple-criteria using weighted linear optimization. Computer and Operations Research, 33(3), 695-700.
Srikant, R., & Agrawal, R. (1995). Mining generalized association rules. Proceedings of the 21th International Conference on Very Large Data Bases (pp. 407–419). Zurich, Switzerland.
Wang, K. and Su, M.Y. (2002). Item Selection by "Hub-Authority" Profit Ranking. Proceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 652-657). Ed- monton, Alberta, Canada
Wang, K., Xu, C. & Liu, B. (1999). Clustering transactions using large item. ACM CIKM International Conference on Information and Knowledge Management, New York (pp. 483-490).
Wong, R. C., Fu, A. W., & Wang, K. (2003).MPIS: Maximal-profit item selection with cross-selling considerations. IEEE International Conference on Data Mining (pp. 371-378). Florida, USA.
Wong, R. C., Fu, A. W., & Wang, K. (2005). Data mining for inventory item selection with cross-selling consideration. Data Mining and Knowledge Discovery, 11(1), 81–112.
Xiao, Y., Zhang, R., & Kaku, I. (2011). A new approach of inventory classification based on loss profit. Expert Systems with Applications, 38(8), 9382–9391.
Yin, Y., Kaku, I., Tang, J., & Zhu, J. M. (2011). Data Mining Concepts, Methods and Applications in Management and Engineering Design. London: Springer.
Zhou, P., and Fan, L. (2007). A note on multi-criteria ABC inventory classification using weighted linear optimization, European Journal of Operational Research, 182(3), 1488-1491.
Brijs, T., Swinnen, G., Vanhoof, K., & Wets, G. (1999).Using association rules for product assortment decisions: A case study. Proceedings of the 5th ACM SIGKDD International Conference on Knowledge discovery & data mining (pp. 254-260). New York, USA.
Brijs, T., Swinnen, G., Vanhoof, K., & Wets, G. (2000). A data mining framework for optimal product selection in retail supermarket data: The generalized PROFSET model. Proceedings of the 6th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (pp. 300-304). New York, USA.
Bala, P. K. (2008). Identification of purchase dependencies in retail sale. International Journal of Strategic Management, 8(2), 75–83.
Bala, P. K., Sural, S., & Banerjee, R. N. (2010). Association rule for purchase dependence in multi-item inventory. Production Planning and Control, 21(3), 274–285.
Bala, P. K. (2012). An inventory replenishment model under purchase dependency in retail sale. International Journal of Computer Applications, 37(10), 43–48.
Chase, R. B., Aquilano, N. J., & Jacobs, F. R. (1998). Production & operations management manufacturing & services (8thed.). McGraw-Hill companies.
Cheng, Y. (2005). Genetic algorithm for item selection with cross-selling considerations. Proceedings of the 4th International Conference on Machine Learning and Cybernetics. China. (pp. 3293-3298).
Cohen, M. A., & Ernst, R. (1988). Multi-item classification and generic inventory stock control Policies. Production & Inventory Management Journal, 29(3), 6–8.
Flores, B. E., & Whybark, D. C. (1987). Implementing multiple criteria ABC analysis. Journal of Operations Management, 7(1 & 2), 79–85.
Kaku, I. (2004). A data mining framework for classification of inventories. Proceedings of the 5thAsia Pacific Industrial Engineering & Management Systems (pp. 450-455). Japan.
Kaku, I., & Xiao, Y. (2008). A new algorithm of inventory classification based on the association rules. International Journal of Services Sciences, 1(2), 148–163.
Kleinberg, J. (1998). Authoritative sources in a hyperlinked environment. Proceedings of the 9th ACM-SIAM Symposium on Discrete Algorithms(pp. 668-677).San Francisco, California, USA.
Lenard, J. D., & Roy, B. (1995). Multi-item inventory control: A multicriteria view. European Journal of Operational Research, 87(3), 685–692.
Mittal, M., Pareek, S., & Agarwal, R. (2014). Efficient ordering policy for imperfect quality items using association rule mining. In Encyclopedia of information science and technology (3rd ed., pp. 773–786). United states: Information Science publishing.
Mittal, M., Pareek, S., & Agarwal, R. (2015a). Loss profit estimation using association rule mining with clustering. Management Science Letters, 5(2), 167–174.
Mittal, M., Pareek, S., & Agarwal, R. (2015b). Ordering policy using temporal association rule mining. International Journal of Data Science, 1(2), 157-171.
Mittal, M., Pareek, S., & Agarwal, R. (2016). Loss profit estimation using temporal association rule mining. International Journal of Business Analytics, 3(1), 45-57.
Ng, W. L. (2007). A simple classifier for multiple criteria ABC analysis. European Journal of Operational Research, 177(1), 344-353.
Ozan, C., & Mustafa, S.C. (2008). A web-based decision support system for multi-criteria inventory classification using fuzzy AHP methodology. Expert Systems with Applications, 35(3), 1367–1378.
Ramanathan, R. (2006). ABC inventory classification with multiple-criteria using weighted linear optimization. Computer and Operations Research, 33(3), 695-700.
Srikant, R., & Agrawal, R. (1995). Mining generalized association rules. Proceedings of the 21th International Conference on Very Large Data Bases (pp. 407–419). Zurich, Switzerland.
Wang, K. and Su, M.Y. (2002). Item Selection by "Hub-Authority" Profit Ranking. Proceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 652-657). Ed- monton, Alberta, Canada
Wang, K., Xu, C. & Liu, B. (1999). Clustering transactions using large item. ACM CIKM International Conference on Information and Knowledge Management, New York (pp. 483-490).
Wong, R. C., Fu, A. W., & Wang, K. (2003).MPIS: Maximal-profit item selection with cross-selling considerations. IEEE International Conference on Data Mining (pp. 371-378). Florida, USA.
Wong, R. C., Fu, A. W., & Wang, K. (2005). Data mining for inventory item selection with cross-selling consideration. Data Mining and Knowledge Discovery, 11(1), 81–112.
Xiao, Y., Zhang, R., & Kaku, I. (2011). A new approach of inventory classification based on loss profit. Expert Systems with Applications, 38(8), 9382–9391.
Yin, Y., Kaku, I., Tang, J., & Zhu, J. M. (2011). Data Mining Concepts, Methods and Applications in Management and Engineering Design. London: Springer.
Zhou, P., and Fan, L. (2007). A note on multi-criteria ABC inventory classification using weighted linear optimization, European Journal of Operational Research, 182(3), 1488-1491.