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Original Articles

Multi-objective parallel robotic dispensing planogram optimisation using association rule mining and evolutionary algorithms

, , , &
Pages 799-814 | Received 14 Dec 2016, Accepted 06 Mar 2018, Published online: 17 May 2018

References

  • Agarwal, R., and R. Srikant. 1994. “Fast Algorithms for Mining Association Rules.” In Proc. of the 20th VLDB Conference, 487–499.
  • Agrawal, R., T. Imieliński, and A. Swami. 1993a. “Database Mining: A Performance Perspective.” Knowledge and Data Engineering, IEEE Transactions On 5 (6): 914–925. doi:10.1109/69.250074.
  • Agrawal, R., T. Imieliński, and A. Swami. 1993b. “Mining Association Rules between Sets of Items in Large Databases.” Acm Sigmod Record 22: 207–216. ACM. doi:10.1145/170036.
  • Agrawal, R., T. Imieliński, and A. Swami. 1993c. ““Mining Association Rules between Sets of Items in Large Databases.” ACM SIGMOD Record 22 (2): 207–216. doi:10.1145/170036.
  • Ahmadi, E., M. Zandieh, M. Farrokh, and S. M. Emami. 2016. “A Multi Objective Optimization Approach for Flexible Job Shop Scheduling Problem under Random Machine Breakdown by Evolutionary Algorithms.” Computers & Operations Research 73: 56–66. doi:10.1016/j.cor.2016.03.009.
  • Alikar, N., S. M. Mousavi, R. A. R. Ghazilla, M. Tavana, and E. U. Olugu. 2016. “Application of the NSGA-II Algorithm to a Multi-Period Inventory-Redundancy Allocation Problem in a Series-Parallel System.” Reliability Engineering & System Safety 160: 1-10.
  • Aloysius, G., and D. Binu. 2013. “An Approach to Products Placement in Supermarkets Using PrefixSpan Algorithm.” Journal of King Saud University-Computer and Information Sciences 25 (1): 77–87. doi:10.1016/j.jksuci.2012.07.001.
  • Amiri, M., and M. Khajeh. 2016. “Developing a Bi-Objective Optimization Model for Solving the Availability Allocation Problem in Repairable Series–Parallel Systems by NSGA II.” Journal of Industrial Engineering International 12 (1): 61–69. doi:10.1007/s40092-015-0128-4.
  • Anandhavalli, M., S. K. Sudhanshu, A. Kumar, and M. K. Ghose. 2009. “Optimized Association Rule Mining Using Genetic Algorithm.” Advances in Information Mining 1 (2) : 1-4.
  • Bouker, S., R. Saidi, S. B. Yahia, and E. M. Nguifo. 2012. “Ranking and Selecting Association Rules Based on Dominance Relationship.” In Tools with Artificial Intelligence (ICTAI), 2012 IEEE 24th International Conference on, Vol. 1, 658–665. IEEE.
  • Bouker, S., R. Saidi, S. B. Yahia, and E. M. Nguifo. 2013. “Towards a Semantic and Statistical Selection of Association Rules.” arXiv Preprint arXiv:1305.5824.
  • Bouker, S., R. Saidi, S. B. Yahia, and E. M. Nguifo. 2014. “Mining Undominated Association Rules Through Interestingness Measures.” International Journal on Artificial Intelligence Tools 23 (04): 1-8. doi:10.1142/S0218213014600112.
  • Dauod, H., L. Debiao, S. W. Yoon, and K. Srihari. 2016. “Multi-Objective Optimization of the Order Scheduling Problem in Mail-Order Pharmacy Automation Systems.” The International Journal of Advanced Manufacturing Technology 1–11. doi:10.1007/s00170-016-9123-1
  • Deb, K., A. Pratap, S. Agarwal, and T. A. M. T. Meyarivan. 2002. “A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II.” IEEE Transactions on Evolutionary Computation 6 (2): 182–197. doi:10.1109/4235.996017.
  • Fournier-Viger, P., J. C.-W. Lin, B. Vo, T. T. Chi, J. Zhang, and H. B. Le. 2017. “A Survey of Itemset Mining.” Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 7 (4): 1-18.
  • Gaul, W., and L. Schmidt-Thieme. 2001. “Mining Generalized Association Rules for Sequential and Path Data.” In Data Mining, 2001. ICDM 2001, Proceedings IEEE International Conference on, 593–596. IEEE.
  • Geismar, H. N., M. Dawande, B. P. S. Murthi, and C. Sriskandarajah. 2015. “Maximizing Revenue Through Two-Dimensional Shelf-Space Allocation.” Production and Operations Management 24 (7): 1148–1163. doi:10.1111/poms.12316.
  • Gen, M., and L. Lin. 2014. “Multiobjective Evolutionary Algorithm for Manufacturing Scheduling Problems: State-Of-The-Art Survey.” Journal of Intelligent Manufacturing 25 (5): 849–866. doi:10.1007/s10845-013-0804-4.
  • Ghosh, A., and B. Nath. 2004. “Multi-Objective Rule Mining Using Genetic Algorithms.” Information Sciences 163 (1–3): 123–133. doi:10.1016/j.ins.2003.03.021.
  • Ghosh, S., S. Biswas, D. Sarkar, and P. P. Sarkar. 2010. “Mining Frequent Itemsets Using Genetic Algorithm.” International Journal of Artificial Intelligence & Applications (IJAIA) 1(4): 133-143.
  • Grahne, G., and J. Zhu. 2005. “Fast Algorithms for Frequent Itemset Mining Using FP-trees.” Knowledge and Data Engineering, IEEE Transactions On 17 (10): 1347–1362. doi:10.1109/TKDE.2005.166.
  • Greb, E., and M. Rios. 2009. “Robots: The Next Phase in Pharmaceutical Automation.” Pharmaceutical Technology 33: 9.
  • Han, J., H. Cheng, D. Xin, and X. Yan. 2007. “Frequent Pattern Mining: Current Status and Future Directions.” Data Mining and Knowledge Discovery 15 (1): 55–86. doi:10.1007/s10618-006-0059-1.
  • Han, J., J. Pei, and Y. Yin. 2000. “Mining Frequent Patterns without Candidate Generation.” ACM SIGMOD Record 29 (2): 1–12. doi:10.1145/335191.
  • Hansen, J. M., S. Raut, and S. Swami. 2010. “Retail Shelf Allocation: A Comparative Analysis of Heuristic and Meta-Heuristic Approaches.” Journal of Retailing 86 (1): 94–105. doi:10.1016/j.jretai.2010.01.004.
  • Hegland, M. 2005. “The Apriori Algorithm–A Tutorial.” Mathematics and Computation in Imaging Science and Information Processing 11: 209–262.
  • Hipp, J., U. Güntzer, and G. Nakhaeizadeh. 2000. “Algorithms for Association Rule Mininga General Survey and Comparison.” ACM Sigkdd Explorations Newsletter 2 (1): 58–64. doi:10.1145/360402.
  • Jenkins, A., and S. F. Eckel. 2012. “Analyzing Methods for Improved Management of Workflow in an Outpatient Pharmacy Setting.” American Journal of Health-System Pharmacy 69: 11. doi:10.2146/ajhp110389.
  • Kavousi-Fard, A., and T. Niknam. 2013. “Considering Uncertainty in the Multi-Objective Stochastic Capacitor Allocation Problem Using a Novel Self Adaptive Modification Approach.” Electric Power Systems Research 103: 16–27. doi:10.1016/j.epsr.2013.04.010.
  • Khader, N., A. Lashier, and S. W. Yoon. 2016. “Pharmacy Robotic Dispensing and Planogram Analysis Using Association Rule Mining with Prescription Data.” Expert Systems with Applications 57: 296–310. doi:10.1016/j.eswa.2016.02.045.
  • Khader, N., and S. W. Yoon. 2014. “Frequent Pattern Mining in a Pharmacy Database through the Use of Hadoop.” In Proceedings of the 3rd Annual World Conference of the Society for Industrial and Systems Engineering, Vol. 3, San Antonio, Texas, USA.
  • Khader, N., and S. W. Yoon. 2015. “The Performance of Sequential and Parallel Implementations of FP-growth in Mining a Pharmacy Database.” In Proceedings of the 2015 Industrial and Systems Engineering Research Conference, Nashville, Tennessee, USA.
  • Klemettinen, M., H. Mannila, P. Ronkainen, H. Toivonen, and A. Inkeri Verkamo. 1994. “Finding Interesting Rules from Large Sets of Discovered Association Rules.” In Proceedings of the Third International Conference on Information and Knowledge Management, 401–407. ACM.
  • Knowles, J., and D. Corne. 1999. “The Pareto Archived Evolution Strategy: A New Baseline Algorithm for Pareto Multiobjective Optimisation.” In Evolutionary Computation, 1999. CEC 99. Proceedings of the 1999 Congress on, Vol. 1, 98–105. IEEE.
  • Kotsiantis, S., and D. Kanellopoulos. 2006. “Association Rules Mining: A Recent Overview.” GESTS International Transactions on Computer Science and Engineering 32 (1): 71–82.
  • Li, D., and S. W. Yoon. 2015. “A Novel Fill-Time Window Minimisation Problem and Adaptive Parallel Tabu Search Algorithm in Mail-Order Pharmacy Automation System.” International Journal of Production Research 53 (14): 4189–4205. doi:10.1080/00207543.2014.985392.
  • Mannila, H., H. Toivonen, and A. Inkeri Verkamo. 1997. “Discovery of Frequent Episodes in Event Sequences.” Data Mining and Knowledge Discovery 1 (3): 259–289. doi:10.1023/A:1009748302351.
  • McGarry, K. 2005. “A Survey of Interestingness Measures for Knowledge Discovery.” The Knowledge Engineering Review 20 (01): 39–61. doi:10.1017/S0269888905000408.
  • Mei, K., L. Debiao, S. W. Yoon, and J.-H. Ryu. 2016. “Multi-Objective Optimization of Collation Delay and Makespan in Mail-Order Pharmacy Automated Distribution System.” The International Journal of Advanced Manufacturing Technology 83 (1–4): 475–488. doi:10.1007/s00170-015-7555-7.
  • Mousavi, S. M., N. Alikar, S. T. A. Niaki, and A. Bahreininejad. 2015. “Two Tuned Multi-Objective Meta-Heuristic Algorithms for Solving a Fuzzy Multi-State Redundancy Allocation Problem under Discount Strategies.” Applied Mathematical Modelling 39 (22): 6968–6989. doi:10.1016/j.apm.2015.02.040.
  • Nasreen, S., M. A. Azam, K. Shehzad, U. Naeem, and M. A. Ghazanfar. 2014. “Frequent Pattern Mining Algorithms for Finding Associated Frequent Patterns for Data Streams: A Survey.” Procedia Computer Science 37: 109–116. doi:10.1016/j.procs.2014.08.019.
  • Obeis, N. T., and W. Bhaya. 2017. “A Survey on Association Rule Mining Approaches for Malicious Detection.” Journal of Engineering and Applied Sciences 12 (21): 5394–5398.
  • Ozcan, T., and S. Esnaf. 2013. “A Discrete Constrained Optimization Using Genetic Algorithms for A Bookstore Layout.” International Journal of Computational Intelligence Systems 6 (2): 261–278. doi:10.1080/18756891.2013.768447.
  • Papageorgiou, L. G., G. E. Rotstein, and N. Shah. 2001. “Strategic Supply Chain Optimization for the Pharmaceutical Industries.” Industrial & Engineering Chemistry Research 40 (1): 275–286. doi:10.1021/ie990870t.
  • Qodmanan, H. R., M. Nasiri, and B. Minaei-Bidgoli. 2011. “Multi Objective Association Rule Mining with Genetic Algorithm without Specifying Minimum Support and Minimum Confidence.” Expert Systems with Applications 38 (1): 288–298. doi:10.1016/j.eswa.2010.06.060.
  • Saggar, M., A. K. Agrawal, and A. Lad. 2004. “Optimization of Association Rule Mining Using Improved Genetic Algorithms.” In Systems, Man and Cybernetics, 2004 IEEE International Conference on, Vol. 4, 3725–3729. IEEE.
  • Silverstein, C., S. Brin, R. Motwani, and J. Ullman. 2000. “Scalable Techniques for Mining Causal Structures.” Data Mining and Knowledge Discovery 4 (2–3): 163–192. doi:10.1023/A:1009891813863.
  • Sudeng, S., and N. Wattanapongsakorn. 2016. “A Knee-Based Multi-Objective Evolutionary Algorithm: An Extension to Network System Optimization Design Problem.” Cluster Computing 19 (1): 411–425. doi:10.1007/s10586-015-0492-2.
  • Wang, H., D. M. Serhan, and S. W. Yoon. 2016. “Collation Delay Optimization Using Discrete Event Simulation in Mail-Order Pharmacy Automation Systems.” In Proceedings of the 2016 Industrial and Systems Engineering Research Conference, Anaheim, California, USA.
  • Wang, H., and S. W. Yoon. 2014. “Evaluation and Optimization of Automatic Drug Dispensing/Filling System.” In Proceedings of the 3rd Annual World Conference of the Society for Industrial and Systems Engineering, San Antonio, Texas, USA.
  • Wang, H., and S. W. Yoon. 2016. “Drug Dispenser Replenishment Optimization via Mixed Integer Programming in Central Fill Pharmacy Systems.” In Proceedings of the 2016 Industrial and Systems Engineering Research Conference, Anaheim, California, USA.
  • Wu, X., V. Kumar, J. R. Quinlan, J. Ghosh, Q. Yang, H. Motoda, G. J. McLachlan, et al. 2008. “Top 10 Algorithms in Data Mining.” Knowledge and Information Systems 14 (1): 1–37. doi:10.1007/s10115-007-0114-2.
  • Yan, X., C. Zhang, and S. Zhang. 2009. “Genetic Algorithm-Based Strategy for Identifying Association Rules without Specifying Actual Minimum Support.” Expert Systems with Applications 36 (2): 3066–3076. doi:10.1016/j.eswa.2008.01.028.
  • Yang, M.-H. 2001. “An Efficient Algorithm to Allocate Shelf Space.” European Journal of Operational Research 131 (1): 107–118. doi:10.1016/S0377-2217(99)00448-8.
  • Zhang, W., K. Cao, S. Liu, and B. Huang. 2016. “A Multi-Objective Optimization Approach for Health-Care Facility Location-Allocation Problems in Highly Developed Cities Such as Hong Kong.” Computers, Environment and Urban Systems 59: 220–230. doi:10.1016/j.compenvurbsys.2016.07.001.
  • Zhao, X., C. Yun, X. Liu, and W. Wang. 2008. “Modeling and Simulation of the Automated Pharmacy System.” In Intelligent Computation Technology and Automation (ICICTA), 2008 International Conference on, Vol. 1, 621–625. IEEE.
  • Zitzler, E., M. Laumanns, and L. Thiele. 2001. “SPEA2: Improving the Strength Pareto Evolutionary Algorithm.” In TIK-report, 103. Eidgenössische Technische Hochschule Zürich (ETH), Institut für Technische Informatik und Kommunikationsnetze (TIK).

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