Factor selection of product quotation with incomplete covering rough set

References

• Atef, M., and A. E. F. El Atik. 2021. “Some Extensions of Covering-Based Multigranulation Fuzzy Rough Sets from new Perspectives.” Soft Computing 25: 6633–6651.
   Web of Science ®Google Scholar
• Bonikowski, Z., E. Bryniarski, and U. Wybraniec. 1998. “Extensions and Intentions in the Rough Set Theory.” Information Sciences 107: 149–167.
   Web of Science ®Google Scholar
• Bramham, J., B. Maccarthy, and J. Guinery. 2005. “Managing Product Variety in Quotation Processes.” Journal of Manufacturing Technology Management 16 (4): 411–431.
   Google Scholar
• Chen, K., X. Feng, and B. Zhang. 2003. “Development of Computer-Aided Quotation System for Manufacturing Enterprises Using Axiomatic Design.” International Journal of Production Research 41 (1): 171–191.
   Web of Science ®Google Scholar
• Chen, D. G., C. Z. Wang, and Q. H. Hu. 2007. “A New Approach to Attribute Reduction of Consistent and Inconsistent Covering Decision System.” Information Sciences 179: 3500–3518.
   Google Scholar
• Clark, P. G., J. W. Grzymala-Busse, and W. Rzasa. 2014. “Mining Incomplete Data with Singleton, Subset and Concept Probabilistic Approximations.” Information Sciences 280: 368–384.
   Web of Science ®Google Scholar
• Dai, J. H. 2013. “Rough Set Approach to Incomplete Numerical Data.” Information Sciences 241: 43–57.
   Web of Science ®Google Scholar
• Dai, J. H., W. T. Wang, and Q. Xu. 2013. “An Uncertainty Measure for Incomplete Decision Tables and Its Applications.” IEEE Transactions on Cybernetics 43 (4): 1277–1289.
   PubMed Web of Science ®Google Scholar
• Dixit, V., A. Chaudhuri, and R. K. Srivast. 2019. “Assessing Value of Customer Involvement in Engineered-to-Order Shipbuilding Projects Using Fuzzy set and Rough Set Theories.” International Journal of Production Research 57 (22): 6943–6962.
   Web of Science ®Google Scholar
• Feng, J. J., and M. Zhang. 2017. “Dynamic Quotation of Leadtime and Price for a Make-to-Order System with Multiple Customer Classes and Perfect Information on Customer Preferences.” European Journal of Operational Research 258 (1): 334–342.
   Web of Science ®Google Scholar
• García-Crespo, Á, B. Ruiz-Mezcua, J. López-Cuadrado, and I. González-Carrasco. 2011. “A Review of Conventional and Knowledge Based Systems for Machining Price Quotation.” Journal of Intelligent Manufacturing 22 (6): 823–841.
   Web of Science ®Google Scholar
• Ge, X., P. Wang, and Z. Q. Yun. 2017. “The Rough Membership Functions on Four Types of Covering-Based Rough Sets and Their Applications.” Information Sciences 390: 1–14.
   Web of Science ®Google Scholar
• Hong, T. P., L. H. Tseng, and S. L. Wang. 2002. “Learning Rules from Incomplete Training Examples by Rough Sets.” Expert Systems with Applications 22: 285–293.
   Web of Science ®Google Scholar
• Hvam, L., S. Pape, and M. K. Nielsen. 2006. “Improving the Quotation Process with Product Configuration.” Computers in Industry 57 (7): 607–621.
   Web of Science ®Google Scholar
• Kryszkiewicz, M. 1998. “Rough set Approach to Incomplete Information Systems.” Information Sciences 112: 39–49.
   Web of Science ®Google Scholar
• Kryszkiewicz, M. 2001. “Comparative Study of Alternative Types of Knowledge Reduction in Consistent Systems.” International Journal of Intelligent Systems 16: 105–120.
   Web of Science ®Google Scholar
• Latkowski, R., and M. Mikolajczyk. 2004. “Data Decomposition and Decision Rule Joining for Classification of Data with Missing Values.” Transactions on Rough Sets 1: 299–320.
   Google Scholar
• Lee, C. H. 2007. “A Hellinger-Based Discretization Method for Numeric Attributes in Classification Learning.” Knowledge-Based Systems 20 (4): 419–425.
   Web of Science ®Google Scholar
• Leung, Y., and D. Li. 2003. “Maximal Consistent Block Technique for Rule Acquisition in Incomplete Information Systems.” Information Sciences 153: 85–106.
   Web of Science ®Google Scholar
• Leung, K. H., C. C. Luk, K. L. Choy, H. Y. Lam, and C. K. M. Lee. 2019. “A B2B Flexible Pricing Decision Support System for Managing the Request for Quotation Process Under Ecommerce Business Environment.” International Journal of Production Research 57 (20): 6528–6551.
   Web of Science ®Google Scholar
• Leung, Y., W. Z. Wu, and W. X. Zhang. 2006. “Knowledge Acquisition in Incomplete Information Systems: A Rough Set Approach.” European Journal of Operational Research 168 (1): 164–180.
   Web of Science ®Google Scholar
• Li, J. R., P. K. Li, and B. T. Shu. 2006. “RMINE: A Rough set Based Data Mining Prototype for the Reasoning of Incomplete Data in Condition-Based Fault Diagnosis.” Journal of Intelligent Manufacturing 17: 163–176.
   Web of Science ®Google Scholar
• Lin, B. Y., X. Y. Zhang, W. H. Xu, and Y. X. Wu. 2020. “Dynamically Updating Approximations Based on Multi-Threshold Tolerance Relation in Incomplete Interval-Valued Decision Information Systems.” Knowledge and Information Systems 62: 1063–1087.
   Web of Science ®Google Scholar
• Liu, X. F., J. H. Dai, J. L. Chen, and C. C. Zhang. 2021. “A Fuzzy α-Similarity Relation-Based Attribute Reduction Approach in Incomplete Interval-Valued Information Systems.” Applied Soft Computing 109: 107593.
   Web of Science ®Google Scholar
• Liu, W., C. Yang, and X. H. Zhou. 2018. “A Network Quotation Framework for Customised Parts Through Rough Requests.” International Journal of Computer Integrated Manufacturing 31 (12): 1220–1234.
   Web of Science ®Google Scholar
• Luo, J. F., H. Fujita, Y. Y. Yao, and K. Y. Qin. 2020. “On Modelling Similarity and Three-Way Decision Under Incomplete Information in Rough set Theory.” Knowledge-Based Systems 191: 1–14.
   Web of Science ®Google Scholar
• Meng, Z. Q., and Z. Z. Shi. 2009. “A Fast Approach to Attribute Reduction in Incomplete Decision Systems with Tolerance Relation-Based Rough Sets.” Information Sciences 179 (16): 2774–2793.
   Web of Science ®Google Scholar
• Meng, Z. Q., and Z. Z. Shi. 2012. “Extended Rough-set-Based Attribute Reduction in Inconsistent Incomplete Decision Systems.” Information Sciences 204: 44–69.
   Web of Science ®Google Scholar
• Mordeson, J. N. 2001. “Rough set Theory Applied to (Fuzzy) Ideal Theory.” Fuzzy Sets and Systems 121: 315–324.
   Web of Science ®Google Scholar
• Nawar, A. S., M. K. El-Bably, and A. E. F. El-Atik. 2020. “Certain Types of Coverings Based Rough Sets with Application.” Journal of Intelligent & Fuzzy Systems 39 (3): 3085–3098.
   Web of Science ®Google Scholar
• Nemeti, A., and B. Denkena. 2014. “Time-oriented Pricing for the Tool and Mould Manufacturing Industry.” Production Engineering 8: 165–173.
   Google Scholar
• Newman, D. J., S. Hettich, C. L. Blake, and C. J. Merz. 1998. UCI Repository of Machine Learning Databases. Irvine, CA: University of California, Department of Information and Computer Science. http://archive.ics.uci.edu/ml/index.php.
   Google Scholar
• Pawlak, Z. 1982. “Rough Sets.” International Journal of Computer & Information Sciences 11 (5): 341–356.
   Web of Science ®Google Scholar
• Qian, Y. H., J. Liang, W. Pedrycz, and C. Y. Dang. 2011. “An Efficient Accelerator for Attribute Reduction from Incomplete Data in Rough Set Framework.” Pattern Recognition 44 (8): 1658–1670.
   Web of Science ®Google Scholar
• Skowron, A., and J. Stepaniuk. 1996. “Tolerance Approximation Spaces.” Fundamenta Informaticae 27: 245–253.
   Google Scholar
• Song, W. Y., X. G. Ming, Y. Han, and Z. Y. Wu. 2013. “A Rough Set Approach for Evaluating Vague Customer Requirement of Industrial Product-Service System.” International Journal of Production Research 51 (22): 6681–6701.
   Web of Science ®Google Scholar
• Stadnicka, D., and R. M. C. Ratnayake. 2018. “Development of Additional Indicators for Quotation Preparation Performance Management: VSM-Based Approach.” Journal of Manufacturing Technology Management 29 (5): 866–885.
   Web of Science ®Google Scholar
• Su, L. R., and W. Zhu. 2018. “Dependence Space of Topology and Its Application to Attribute Reduction.” International Journal of Machine Learning and Cybernetics 9: 691–698.
   Web of Science ®Google Scholar
• Sun, L., X. Y. Zhang, Y. H. Qian, J. C. Xu, and S. G. Zhang. 2019. “Feature Selection Using Neighbourhood Entropy-Based Uncertainty Measures for Gene Expression Data Classification.” Information Sciences 502: 8–41.
   Web of Science ®Google Scholar
• Thangavel, K., and A. Pethalakshmi. 2009. “Dimensionality Reduction Based on Rough Set Theory: A Review.” Applied Soft Computing 9 (1): 1–12.
   Web of Science ®Google Scholar
• Thuy, N. N., and S. Wongthanavasu. 2020. “An Efficient Stripped Cover-Based Accelerator for Reduction of Attributes in Incomplete Decision Tables.” Expert Systems with Applications 143: 113076.
   Web of Science ®Google Scholar
• Thuy, N. N., and S. Wongthanavasu. 2021. “A Novel Feature Selection Method for High-Dimensional Mixed Decision Tables.” IEEE Transactions on Neural Networks and Learning Systems, 1–14.
   Web of Science ®Google Scholar
• Tseng, T. L. B., M. C. Jothishankar, and T. T. Wu. 2004. “Quality Control Problem in Printed Circuit Board Manufacturing, an Extended Rough Set Theory Approach.” Journal of Manufacturing Systems 23 (1): 56–72.
   Web of Science ®Google Scholar
• Villuendas-Rey, Y. 2019. “Maximal Similarity Granular Rough Sets for Mixed and Incomplete Information Systems.” Soft Computing 23: 4617–4631.
   Web of Science ®Google Scholar
• Wang, C. Z., M. W. Shao, B. Q. Sun, and Q. H. Hu. 2015. “An Improved Attribute Reduction Scheme with Covering Based Rough Sets.” Applied Soft Computing 26: 235–243.
   Web of Science ®Google Scholar
• Xu, Y., and S. Z. Hu. 2019. “Extended Rough set Model Based on Modified Data-Driven Valued Tolerance Relation.” Journal of Intelligent & Fuzzy Systems 36: 1615–1625.
   Web of Science ®Google Scholar
• Yazdani, M., D. Pamucar, P. Chatterjee, and S. Chakraborty. 2020. “Development of a Decision Support Framework for Sustainable Freight Transport System Evaluation Using Rough Numbers.” International Journal of Production Research 58 (14): 4325–4351.
   Web of Science ®Google Scholar
• Yin, Y. C., L. T. Zhang, W. Z. Liao, H. W. Niu, and F. Z. Chen. 2019. “A Knowledge Resources Fusion Method Based on Rough Set Theory or Quality Prediction.” Computers in Industry 108: 104–114.
   Web of Science ®Google Scholar
• Yu, Y. G., Y. J. Wang, and Y. Liu. 2020. “Product Quality and Quantity with Responsive Pricing.” International Journal of Production Research, 1–19.
   Web of Science ®Google Scholar
• Zhang, L. L., C. K. M. Lee, and P. Akhtar. 2020. “Towards Customization: Evaluation of Integrated Sales, Product, and Production Configuration.” International Journal of Production Economics 229: 107775.
   Web of Science ®Google Scholar