216
Views
4
CrossRef citations to date
0
Altmetric
Original Articles

Formulation and application of weight-function-based physical programming

, , &
Pages 1628-1650 | Received 01 Apr 2013, Accepted 09 Oct 2013, Published online: 03 Jan 2014

References

  • Carrese, R., H. Winarto, X.D. Li, A. Sobester and S. Ebenezer. 2012. “A comprehensive preference-based optimization framework with application to high-lift aerodynamic design.” Engineering Optimization 44 (10): 1209–1227. doi: 10.1080/0305215X.2011.637558
  • Chica, M., O. Cordon, S. Damas and J. Bautista. 2011. “Including different kinds of preferences in a multi-objective ant algorithm for time and space assembly line balancing on different Nissan scenarios.” Expert Systems with Applications 38 (1): 709–720. doi: 10.1016/j.eswa.2010.07.023
  • Das, I., and J. E. Dennis. 1997. “A closer look at drawbacks of minimizing weighted sums of objectives for Pareto set generation in multicriteria optimization problems.” Structural and Multidisciplinary Optimization 14 (1): 63–69.
  • Das, I. 1997. “Nonlinear multicriteria optimization and robust optimality.” PhD diss. Rice University, Houston, TX.
  • Deb, K., and J. Sundar. 2006. “Reference point based multi-objective optimization using evolutionary algorithms.” International Journal of Computational Intelligence Research 2 (3): 273–286. doi: 10.5019/j.ijcir.2006.67
  • Deb, K., S. Agrawal, A. Pratap, and T. Meyarivan. 2000. “A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II.” In Proceedings of the 6th International Conference on Parallel Problem Solving from Nature, 18–20 September 2000, Paris, Vol. 1917 of Lecture Notes in Computer Science, edited by M. Schoenauer, K. Deb, G. Rudolph, X. Yao, E. Lutton, J. J. Merelo,and H.-P. Schwefel. Berlin: Springer, 849–858.
  • Dong, Z.H., H.S. Ding, F. Jiang, Z.C. Huang and T. Fu. 2012. “Structural parameters optimization of parallel stable platform based on physical programming.” Advances in Design Technology 2: 187–192.
  • Doumpos, M., and C. Zopounidis. 2004. “Developing sorting models using preference disaggregation analysis: An experimental investigation.” European Journal of Operational Research 154 (3): 585–598. doi: 10.1016/S0377-2217(02)00815-9
  • Gong, D. W., J. Sun, and X. F. Ji. 2013. “Evolutionary algorithms with preference polyhedron for interval multi-objective optimization problems.” Information Sciences 233: 141–161. doi: 10.1016/j.ins.2013.01.020
  • Goradia, A., C. Haffner, X. Ning and M. Mutka. 2007. “Optimality framework for Hausdorff tracking using mutational dynamics and physical programming.” In IEEE International Conference on Robotics and Automation, 10–14 April 2007, Roma, Italy, 3476–3481.
  • Khare, V., X. Yao, and K. Deb. 2003. “Performance scaling of multi-objective evolutionary algorithms.” Evolutionary Multi-Criterion Optimization 2632: 376–390. doi: 10.1007/3-540-36970-8_27
  • Kongar, E., and S. M. Gupta. 2009. “Solving the disassembly-to-order problem using linear physical programming.” International Journal of Mathematics in Operational Research 1 (3): 504–531. doi: 10.1504/IJMOR.2009.026279
  • Kongsuwan, P., and S. Shin. 2009. “Integrating physical programming to information security system management.” In 11th International Conference on Advanced Communication Technology, 15–18 February 2009, Phoenix Park, Korea, 143–148.
  • Kovach, J., B. R. Cho, and J. Antony. 2008. “Development of an experiment-based robust design paradigm for multiple quality characteristics using physical programming.” International Journal of Advanced Manufacturing Technology 35 (11–12): 1100–1112. doi: 10.1007/s00170-006-0792-z
  • Kumar, V.V., M. Tripathi, M.K. Pandey and M.K. Tiwari. 2009. “Physical programming and conjoint analysis-based redundancy allocation in multistate systems: A Taguchi embedded algorithm selection and control (TAS&C) approach.” Proceedings of the Institution of Mechanical Engineers Part O—Journal of Risk and Reliability 223 (3): 215–232. doi: 10.1243/1748006XJRR210
  • Lai, X., M. Xie, and K. C. Tan. 2006. “QFD optimization using linear physical programming.” Engineering Optimization 38 (5): 593–607. doi: 10.1080/03052150500448059
  • Li, W., M. J. Zuo, and R. Moghaddass. 2011. “Optimal design of a multi-state weighted series–parallel system using physical programming and genetic algorithms.” Asia-Pacific Journal of Operational Research 28 (4): 543–562. doi: 10.1142/S0217595911003235
  • Liu, R. C., et al., 2013. “A preference multi-objective optimization based on adaptive rank clone and differential evolution.” Natural Computing 12 (1): 109–132. doi: 10.1007/s11047-012-9339-4
  • Luo, Y. Z., G. J. Tang, and G. Parks. 2008. “Multi-objective optimization of perturbed impulsive rendezvous trajectories using physical programming.” Journal of Guidance Control and Dynamics 31 (6): 1829–1832. doi: 10.2514/1.35409
  • Maria, A., C.A. Mattson, A. Ismail-Yahaya and A. Messac. 2003. “Linear physical programming for production planning optimization.” Engineering Optimization 35 (1): 19–37. doi: 10.1080/0305215031000078401
  • McAllister, C.D., T.W. Simpson, K. Hacker, K. Lewis and A. Messac. 2005. “Integrating linear physical programming within collaborative optimization for multiobjective multidisciplinary design optimization.” Structural and Multidisciplinary Optimization 29 (3): 178–189. doi: 10.1007/s00158-004-0481-1
  • Melachrinoudis, E., A. Messac, and H. Min. 2005. “Consolidating a warehouse network: A physical programming approach.” International Journal of Production Economics 97 (1): 1–17. doi: 10.1016/j.ijpe.2004.04.009
  • Messac, A., 1996. “Physical programming: Effective optimization for computational design.” AIAA Journal 34 (1): 149–158. doi: 10.2514/3.13035
  • Messac, A., S. M. Gupta, and B. Akbulut. 1996. “Linear physical programming: A new approach to multiple objective optimization.” Transactions on Operational Research 8 (2): 39–59.
  • Messac, A., and C. A. Mattson. 2002. “Generating well-distributed sets of Pareto points for engineering design using physical programming.” Optimization and Engineering 3 (4): 431–450. doi: 10.1023/A:1021179727569
  • Messac, A., S. Van Dessel, A.A. Mullur and A. Maria. 2004. “Optimization of large-scale rigidified inflatable structures for housing using physical programming.” Structural and Multidisciplinary Optimization 26 (1–2): 139–151. doi: 10.1007/s00158-003-0317-4
  • Messac, A., C. P. Sukam, and E. Melachrinoudis. 2001. “Mathematical and pragmatic perspectives of physical programming.” AIAA Journal 39 (5): 885–893. doi: 10.2514/2.1392
  • Messac, A., and A. Ismail-Yahaya. 2002. “Multiobjective robust design using physical programming.” Structural and Multidisciplinary Optimization 23 (5): 357–371. doi: 10.1007/s00158-002-0196-0
  • Nagrath, D., et al., 2005. “Multiobjective optimization strategies for linear gradient chromatography.” AIChE Journal 51 (2): 511–525. doi: 10.1002/aic.10459
  • Oliveira, E., C. Henggeler Antunes, and A. Gomes. 2013. “A comparative study of different approaches using an outranking relation in a multi-objective evolutionary algorithm.” Computers & Operations Research 40 (6): 1602–1615. doi: 10.1016/j.cor.2011.09.023
  • Pochampally, K. K., and S. M. Gupta. 2012. “Use of linear physical programming and Bayesian updating for design issues in reverse logistics.” International Journal of Production Research 50 (5): 1349–1359. doi: 10.1080/00207543.2011.571933
  • Qi, Y. L., C. C. Cai, and P. Z. Lang. 2013. “Mathematical modeling on multi-stage series crushing ratio distribution based on fuzzy physical programming.” Journal of Coal Science & Engineering 19 (2): 262–267. doi: 10.1007/s12404-013-0224-2
  • Qiu, H.B., Y.Y. Dong, Y. Wang and L. Gao. 2012. “Tolerance optimization design based on physical programming methods and PSO algorithm.” Sustainable Construction Materials and Computer Engineering 346: 584–592.
  • Ramakrishnan, S., and Y. Abu Hasan. 2013. “Fuzzy preference-based multi-objective optimization method.” Artificial Intelligence Review 39 (2): 165–181. doi: 10.1007/s10462-011-9264-4
  • Roy, B. 1991. “The outranking approach and the foundations of ELECTRE methods.” Theory and Decision 31 (1): 49–73. doi: 10.1007/BF00134132
  • Sanchis, J., M.A. Martinez, X. Blasco and G. Reynoso-Meza. 2010. “Modelling preferences in multi-objective engineering design.” Engineering Applications of Artificial Intelligence 23 (8): 1255–1264. doi: 10.1016/j.engappai.2010.07.005
  • Sanchis, J., M. Martinez, and X. Blasco. 2008. “Multi-objective engineering design using preferences.” Engineering Optimization 40 (3): 253–269. doi: 10.1080/03052150701693057
  • Schott, J. R. 1995. “Fault tolerant design using single and multicriteria genetic algorithm optimization.” MS diss. Massachusetts Institute of Technology, Cambridge, MA.
  • Siraj, S., L. Mikhailov, and J. A. Keane. 2012. “Preference elicitation from inconsistent judgments using multi-objective optimization.” European Journal of Operational Research 220 (2): 461–471. doi: 10.1016/j.ejor.2012.01.049
  • Soylu, B. and S. K. Ulusoy. 2011. “A preference ordered classification for a multi-objective max–min redundancy allocation problem.” Computers & Operations Research 38 (12): 1855–1866. doi: 10.1016/j.cor.2011.02.024
  • Tappeta, R.V., J.E. Renaud, A. Messac and G.J. Sundararaj. 2000. “Interactive physical programming: Tradeoff analysis and decision making in multicriteria optimization.” AIAA Journal 38 (5): 917–926. doi: 10.2514/2.1048
  • Trautmann, H., and J. Mehnen. 2009. “Preference-based Pareto optimization in certain and noisy environments.” Engineering Optimization 41 (1): 23–38. doi: 10.1080/03052150802347926
  • Wang, T., X. Chen, and Y. Lin. 2011. “Multi-objective optimization based on the integration of linear physical programming within analytical target cascading.” In 4th International Conference on Biomedical Engineering and Informatics (BMEI), 15–17 October 2011, Shanghai, PR China, 2286–2289.
  • Wozniak, P. 2011. “Preferences in multi-objective evolutionary optimisation of electric motor speed control with hardware in the loop.” Applied Soft Computing 11 (1): 49–55. doi: 10.1016/j.asoc.2009.10.015
  • Xiong, J., K.W. Yang, J. Liu, Q.S. Zhao and Y.W. Chen. 2012. “A two-stage preference-based evolutionary multi-objective approach for capability planning problems.” Knowledge-Based Systems 31: 128–139. doi: 10.1016/j.knosys.2012.02.003
  • Zhang, X., H. Z. Huang, and L. F. Yu. 2006. “Fuzzy preference based interactive fuzzy physical programming and its application in multi-objective optimization.” Journal of Mechanical Science and Technology 20 (6): 731–737. doi: 10.1007/BF02915937
  • Zhou, J. H., et al. 2012. “Multidisciplinary collaborative satisfaction negotiation based on the physical programming method in product design.” Mechatronics and Applied Mechanics 157–158: 258–262.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.