An adaptive quantum swarm evolutionary algorithm for partner selection in virtual enterprise

References

• Abdorrahman, H., and T. M. Reza. 2012. “Developing a Hybrid Data Mining Approach Based on Multi-objective Particle Swarm Optimization for Solving a Traveling Salesman Problem.” Journal of Business Economics and Management 13: 951–967.
   Web of Science ®Google Scholar
• Afsarmanesh, H., and C. Analide. 2009. “Virtual Enterprises – Methods and Approaches for Coalition Formation.” International Journal of Production Research 47: 4655–4659.
   Web of Science ®Google Scholar
• Alhazov, A., C. Martin-Vide, and L. Q. Pan. 2003. “Solving a PSPACE – Complete Problem by Recognizing P Systems with Restricted Active Membranes.” Fundamenta Informaticae 58: 67–77.
   Web of Science ®Google Scholar
• Chan, F. T. S., N. Kumar, M. K. Tiwari, H. C. W. Lau, and K. L. Choy. 2008. “Global Supplier Selection a Fuzzy-AHP Approach.” International Journal of Production Research 46: 3825–3857.
   Web of Science ®Google Scholar
• Chaturvedi, K. T., M. Pandit, and L. Srivastava. 2009. “Particle Swarm Optimization with Time Varying Acceleration Coefficients for Non-convex Economic Power Dispatch.” Electrical Power and Energy Systems 31: 249–257.
   Web of Science ®Google Scholar
• Chen, J. Y., M. H. Chiang, and R. S. Guo. 2013. “Partner Selection Model for Design Chain Collaboration.” International Journal of Production Research 51: 1131–1145.
   Web of Science ®Google Scholar
• Chen, Y. Y., and J. T. Lin. 2009. “A Modified Particle Swarm Optimization for Production Planning Problems in the TFT Array Process.” Expert Systems with Applications 36: 12264–12271.
   Web of Science ®Google Scholar
• Chen, A. L., G. K. Yang, and Z. M. Wu. 2008. “Production Scheduling Optimization Algorithm for the Hot Rolling Processes.” International Journal of Production Research 46: 1955–1973.
   Web of Science ®Google Scholar
• Coelho, L. D. S., and V. C. Mariani. 2009. “A Novel Chaotic Particle Swarm Optimization Approach using Henon Map and Implicit Filtering Local Search for Economic Load Dispatch.” Chaos, Solitons & Fractals 39: 510–518.
   Web of Science ®Google Scholar
• Crispim, J. A., and J. P. De Sousa. 2009. “Partner Selection in Virtual Enterprises: A Multi-criteria Decision Support Approach.” International Journal of Production Research 47: 4791–4812.
   Web of Science ®Google Scholar
• Crispim, J. A., and J. P. De Sousa. 2010. “Partner Selection in Virtual Enterprises.” International Journal of Production Research 48: 683–707.
   Web of Science ®Google Scholar
• Drissen-Silva, M. V., and R. J. Rabelo. 2009. “A Collaborative Decision Support Framework for Managing the Evolution of Virtual Enterprises.” International Journal of Production Research 47: 4833–4854.
   Web of Science ®Google Scholar
• Feng, W. D., J. C. Chen, and J. Zhao. 2000. “Partner Selection Process and Optimization Model for Virtual Corporations Based on Genetic Algorithms.” Journal of Tsinghua University 40: 120–124.
   Google Scholar
• Feng, X. Y., Y. Wang, H. W. Ge, C. G. Zhou, and Y. C. Liang. 2006. “Quantum-inspired Evolutionary Algorithm for Travelling Salesman Problem.” Lecture Notes in Computer Science 4020: 1363–1367.
   Google Scholar
• Han, K. H., and J. H. Kim. 2000. “Genetic Quantum Algorithm and its Application to Combinatorial Optimization Problem.” In The 2000 IEEE Congress on Evolutionary Computation, 1354–1360. San Diego, CA, USA: IEEE Press.
   Google Scholar
• Hsieh, F. S. 2010. “Combinatorial Reverse Auction Based on Revelation of Lagrangian Multipliers.” Decision Support Systems 48: 323–330.
   Web of Science ®Google Scholar
• Hsieh, F. S., and J. B. Lin. 2012a. “Assessing the Benefits of Group-buying Based Combinatorial Reverse Auctions.” Electronic Commerce Research and Applications 114: 407–419.
   Web of Science ®Google Scholar
• Hsieh, F. S., and J. B. Lin. 2012b. “Virtual Enterprises Partner Selection Based on Reverse Auction.” International Journal of Advanced Manufacturing Technology 62: 847–859.
   Web of Science ®Google Scholar
• Huang, B., C. H. Gao, and L. Chen. 2011. “Partner Selection in a Virtual Enterprise under Uncertain Information about Candidates.” Expert System with Applications 38: 11305–11310.
   Web of Science ®Google Scholar
• Ip, W. H., M. Huang, K. L. Yung, and D. W. Wang. 2003. “Genetic Algorithm Solution for a Risk-based Partner Selection Problem in a Virtual Enterprise.” Computers & Operations Research 30: 213–231.
   Web of Science ®Google Scholar
• Ip, W. H., K. L. Yung, and D. Wang. 2004. “A Branch and Bound Algorithm for Subcontractor Selection in Agile Manufacturing Environment.” International Journal of Production Economics 87: 195–205.
   Web of Science ®Google Scholar
• Jarimo, T., and A. Salo. 2009. “Multicriteria Partner Selection in Virtual Organizations with Transportation Costs and Other Network Interdependencies.” IEEE Transactions O Systems, Man, and Cybernetics, Part C: Applications and Reviews 39: 124–129.
   Web of Science ®Google Scholar
• Jiao, B., Z. G. Lian, and X. S. Gu. 2008. “A Dynamic Inertia Weight Particle Swarm Optimization Algorithm.” Chaos, Solitons & Fractals 37: 698–705.
   Web of Science ®Google Scholar
• Kennedy, J., and R. Eberhart. 1995. “Particle Swarm Optimization.” IEEE Int. Conf. Neural Networks, 1942–1948. Piscataway, NJ: IEEE Service Center.
   Google Scholar
• Mahapatra, S. S., N. R. Nayak, K. Prasanna, and G. S. Beriha. 2011. “A Novel Swarm Optimisation Approach for Risk-based Partner Selection in Virtual Enterprises.” International Journal of Services and Operations Management 10: 52–73.
   Google Scholar
• Mariani, V. C., A. R. K. Duck, F. A. Guerra, L. S. Coelho, and R. V. Rao. 2012. “A Chaotic Quantum-behaved Particle Swarm Approach Applied to Optimization of Heat Exchangers.” Applied Thermal Engineering 42: 119–128.
   Web of Science ®Google Scholar
• Modares, H., A. Alfi, and M.-B. N. Sistani. 2010. “Parameter Estimation of Bilinear Systems Based on an Adaptive Particle Swarm Optimization.” Engineering Applications of Artificial Intelligence 23: 1105–1111.
   Web of Science ®Google Scholar
• Narayanan, A., and M. Moore. 1996. “Quantum-inspired Genetic Algorithm.” In IEEE International Conference on Evolutionary Computation, 61–66. Nagoya, Japan: IEEE Press.
   Google Scholar
• Nickabadi, A., M. M. Ebadzadeh, and R. Safabakhsh. 2011. “A Novel Particle Swarm Optimization Algorithm with Adaptive Inertia Weight.” Applied Soft Computing 11: 3658–3670.
   Web of Science ®Google Scholar
• Niu, S. H., S. K. Ong, and A. Y. C. Nee. 2012. “An Enhanced Ant Colony Optimiser for Multi-attribute Partner Selection in Virtual Enterprises.” International Journal of Production Research 50: 2286–2303.
   Web of Science ®Google Scholar
• Niu, Y. Y., L. Q. Pan, M. J. Perez-Jimenez, and M. R. Font. 2011. “A Tissue P Systems Based Uniform Solution to Tripartite Matching Problem.” Fundamenta Informaticae 109: 1–10.
   Web of Science ®Google Scholar
• OnoltIshdorj, T., A. Leporati, L. Q. Pan, et al. 2010. “Deterministic Solutions to QSAT and Q3SAT by Spiking Neural P Systems with Pre-computed Resources.” Theoretical Computer Science 411: 2345–2358.
   Web of Science ®Google Scholar
• Pan, L. Q., and C. Martin-Vide. 2005. “Solving Multidimensional 0–1 Knapsack Problem by P Systems with Input and Active Membranes.” Journal of Parallel and Distributed Computing 65: 1578–1584.
   Web of Science ®Google Scholar
• Pan, L. Q., and C. Martin-Vide. 2006. “Further Remark on P Systems with Active Membranes and Two Polarizations.” Journal of Parallel and Distributed Computing 66: 867–872.
   Web of Science ®Google Scholar
• Rabbani, M. 2010. “A Multi-objective Particle Swarm Optimization for Project Selection Problem.” Expert Systems with Application 37: 315–321.
   Web of Science ®Google Scholar
• Samanlioglua, F., W. G. Ferrellb, and M. E. Kurzb. 2012. “An Interactive Memetic Algorithm for Production and Manufacturing Problems Modelled as a Multi-objective Travelling Salesman Problem.” International Journal of Production Research 50: 5671–5682.
   Web of Science ®Google Scholar
• Samvedi, A., V. Jain, and F. T. S. Chan. 2013. “Quantifying Risks in a Supply Chain through Integration of Fuzzy AHP and Fuzzy TOPSIS.” International Journal of Production Research 51: 2433–2442.
   Web of Science ®Google Scholar
• Shi, Y., and R. C. Eberhart. 1998. “A Modified Particle Swarm Optimizer.” In IEEE Int. Conf. Evolutionary Computation 69–73. Piscataway, NJ: IEEE Press.
   Google Scholar
• Tao, F., K. Qiao, L. Zhang, Z. Li, and A. Y. C. Nee. 2012. “GA-BHTR: An Improved Genetic Algorithm for Partner Selection in Virtual Manufacturing.” International Journal of Production Research 50: 2079–2100.
   Web of Science ®Google Scholar
• Tao, F., L. Zhang, Z. H. Zhang, and A. Y. C. Nee. 2010. “A Quantum Multi-agent Evolutionary Algorithm for Selection of Partners in a Virtual Enterprise.” CIRP Annals-Manufacturing Technology 59: 485–488.
   Web of Science ®Google Scholar
• Wang, Y., X. Y. Feng, Y. X. Huang, D. B. Pu, W. G. Zhou, Y. C. Liang, and C. G. Zhou. 2007. “A Novel Quantum Swarm Evolutionary Algorithm and Its Applications.” Neurocomputing 70: 633–640.
   Web of Science ®Google Scholar
• Wang, Z. J., X. F. Xu, and D. C. Zhan. 2009. “Genetic Algorithm for Collaboration Cost Optimization-oriented Partner Selection in Virtual Enterprise.” International Journal of Production Research 47: 859–881.
   Web of Science ®Google Scholar
• Xiao, J. H., and B. L. Liu. 2009. “Quantum Swarm Evolutionary Algorithm with Time-varying Acceleration Coefficients for Partner Selection in Virtual Enterprise.” In Fourth International Conference on Bio-Inspired Computing, 1–6. Beijing, China: IEEE Press.
   Google Scholar
• Xiao, R. B., Z. Y. Cai, and X. H. Zhang. 2012. “An Optimization Approach to Risk Decision-making of Closed-loop Logistics Based on SCOR Model.” Optimization: A Journal of Mathematical Programming and Operations Research 61: 1221–1251.
   Google Scholar
• Xiao, J. H., J. Xu, Z. H. Chen, K. Zhang, and L. Q. Pan. 2009. “A Hybrid Quantum Chaotic Swarm Evolutionary Algorithm for DNA Encoding.” Computers and Mathematics with Applications 57: 1949–1958.
   Web of Science ®Google Scholar
• Yang, J. A., B. Li, Z. Q. Zhuang, and Z. F. Zhong. 2003. “Quantum Genetic Algorithm and Its Application Research in Blind Source Separation.” Mini-Micro System 24: 1518–1523.
   Google Scholar
• Yao, Z., J. Liu, and Z. J. Wu. 2009. “An Integrated Optimization Algorithm of GA and ACA-based Approaches for Modelling Virtual Enterprise Partner Selection.” The DATA BASE for Advances in Information Systems 40: 37–56.
   Web of Science ®Google Scholar
• Ye, F., and Y. N. Li. 2009. “Group Multi-attribute Decision Model to Partner Selection in the Formation of Virtual Enterprise under Incomplete Information.” Expert Systems with Applications 36: 9350–9357.
   Web of Science ®Google Scholar
• Yeh, W. C., and M. C. Chuang. 2011. “Using Multi-objective Genetic Algorithm for Partner Selection in Green Supply Chain Problems.” Expert Systems with Applications 38: 4244–4253.
   Web of Science ®Google Scholar
• Zeng, Z. B., Y. Li, and W. Zhu. 2006. “Partner Selection with a Due Date Constraint in Virtual Enterprises.” Applied Mathematics and Computation 175: 1353–1365.
   Web of Science ®Google Scholar
• Zhang, G. X., C. X. Liu, and H. N. Rong. 2010. “Analyzing Radar Emitter Signals with Membrane Algorithms.” Mathematical and Computer Modelling 52: 1997–2010.
   Web of Science ®Google Scholar
• Zhao, Q., and R. B. Xiao. 2009. “Partners Selection Problem in Virtual Enterprise Based on Improve Particle Swarm Optimization Algorithm.” Industrial Engineering and Management 14: 38–42.
   Google Scholar
• Zhao, Q., X. H. Zhang, and R. B. Xiao. 2008. “Particle Swarm Optimization Algorithm for Partner Selection in Virtual Enterprise.” Progress in Natural Science 18: 1445–1452.
   Web of Science ®Google Scholar