Home| Contact Us| New Journals| Browse Journals| Journal Prices| For Authors|

Print ISSN: 2230 – 8776
Online ISSN:


  About JISM
  DLINE Portal Home
Home
Aims & Scope
Editorial Board
Current Issue
Next Issue
Previous Issue
Sample Issue
Upcoming Conferences
Self-archiving policy
Alert Services
Be a Reviewer
Publisher
Paper Submission
Subscription
Contact us
 
  How To Order
  Order Online
Price Information
Request for Complimentary
Print Copy
 
  For Authors
  Guidelines for Contributors
Online Submission
Call for Papers
Author Rights
 
 
RELATED JOURNALS
Journal of Digital Information Management (JDIM)
Journal of Multimedia Processing and Technologies (JMPT)
International Journal of Web Application (IJWA)

 

 
Journal of Information & Systems Management (JISM)

Generalized Scalar Systems using Objective Programming
Leonid Kirilov, Krasimira Genova, Vassil Guliashki and Peter Zhivkov
Inst. of Information and Communication Technologies - BAS Acad. George Bonchev Str bl. 21113 Sofia, Bulgaria., 2ZH Software Ltd., 1000 Sofia, Bulgaria
Abstract: In the objective programming, the issues are normally solved using many interactive models which uses the Generalized Scalar Method. The issues relating to the scalar are solved by using General Scalar Interactive Method. We have used the customized environment for implementing the methods. It is possible to modify the multi-objective issues using the interactive methods to get solutions. We also use the DM preference, using implicit ways.
Keywords: Multiple Objectives, Optimization, Software
DOI:https://doi.org/10.6025/jism/2022/12/3/72-77
Full_Text   PDF 884 KB   Download:   116  times
References:

[1] Steuer, R. (1986). Multiple Criteria Optimization: Theory, Computation and Application. John Wiley & Sons: New York, USA.
[2] Miettinen, K. (1999). Nonlinear Multiobjective Optimization. Kluwer Academic Publishers: Boston.
[3] Ehrgott, M. (2006) A discussion of scalarization techniques for multiple objective integer programming. Annals of Operations Research, 147, 343–360 [DOI: 10.1007/s10479-006-0074-z].
[4] Wierzbicki, A. (1999) Reference point approaches. In: Multicriteria Decision Making: Advances in MCDM Models, Algorithms, Theory and Applications (edited by T. Gal et al.). Kluwer Academic Publishers: Boston, pp. 91–99.
[5] Nakayama, H. & Sawaragi, Y. (1984) Satisficing trade-off method for multiobjective programming. In: Lecture Notes in Economics and Mathematical Systems (edited by M. Grauer & A. Wierzbicki). Springer Verlag: Berlin, 229, 113–122 [DOI: 10.1007/978-3-662-00184-4_13].
[6] Korhonen, P. & Laakso, J. (1986) Solving generalised goal programming problems using a visual interactive approach. European Journal of Operational Research, 26, 355–363 [DOI: 10.1016/0377-2217(86)90137-2].
[7] Korhonen, P. (1997). “Reference Direction Approach to Multiple Objective Linear Programming: Historical Overview”, Essay in Decision Making: A Volume in Honour of Stanley Zionts (M. Karwan, J. Spronk, J. Wallenius – Eds.). Springer-Verlag: Berlin, pp. 74–92.
[8] Narula, S.C., Kirilov, L. & Vassilev, V. (1994) Reference direction approach for solving multiple objective nonlinear problems. IEEE Transactions on Systems, Man, and Cybernetics, 24, 804–806 [DOI: 10.1109/21.293497].
[9] Vassilev, V. & Narula, S.C. (1993) A reference direction algorithm for solving multiple objective integer linear programming problems. Journal of the Operational Research Society, 44, 1201–1209 [DOI: 10.1057/jors.1993.199].
[10] Luque, M., Ruiz, F. & Miettinen, K. (2011) Global formulation for interactive multiobjective optimization. OR Spectrum, 33, 27–48 [DOI: 10.1007/s00291-008-0154-3].
[11] Vassileva, M. (2006) Generalized interactive algorithm of multiobjective optimization. Problems of Engineering Cybernetics and Robotics, 50, 54–64.
[12] Benayoun, R., de Montgolfier, J., Tergny, J. & Laritchev, O. (1971) Linear programming with multiple objective functions: Step method (STEM). Mathematical Programming, 1, 366–375 [DOI: 10.1007/BF01584098].
[13] Steuer, R.E. & Choo, E. (1983) An interactive weighted Tchebycheff procedure for multiple objective programming. Mathematical Programming, 26, 326–344 [DOI: 10.1007/BF02591870].
[14] Nakayama, H. & Sawaragi, Y. (1984) Satisficing trade-off method for multiobjective programming. Lecture Notes in Economics and Mathematical Systems, 229, 113–122 [DOI: 10.1007/978-3-662-00184-4_13].
[15] Buchanan, J.T. (1997) A naive approach for solving MCDM problems: The GUESS method. Journal of the Operational Research Society, 48, 202–206 [DOI: 10.1057/palgrave.jors.2600349].
[16] Wierzbicki, A.P. (1980) The use of reference objectives in multiobjective optimization. In: Lecture Notes in Economics and Mathematical Systems, 177, 468–486 [DOI: 10.1007/978-3-642-48782-8_32].
[17] Genova, K., Kirilov, L. & Guljashki, V. (2013) New reference- neighbourhood scalarization problem for multiobjective integer programming. Cybernetics and Information Technologies, 13, 104–114 [DOI: 10.2478/cait-2013-0010].
[18] Kaliszewski, I. (2004) Out of the mist—Towards decision-makerfriendly multiple criteria decision making support. European Journal of Operational Research, 158, 293–307 [DOI: 10.1016/j.ejor.2003.06.005].
[19] Haimes, Y., Lasdon, L.S. & Wismer, D.A. (1971) On a bicriterion formulation of the problems of integrated system identification and system optimization. IEEE Transactions on Systems, Man and Cybernetics, 1, 296–297.
[20] Miettinen, K. & M?kel?, M.M. (2002) On scalarizing functions in multiobjective optimization. OR Spectrum, 24, 193–213 [DOI: 10.1007/s00291-001-0092-9].
[21] Vassileva, M. (2000) Scalarizing problems of multiobjective linear programming problems. Problems of Engineering, Cybernetics and Robotics, 50, 54–64.
[22] Vassileva, M., Genova, K. & Vassilev, V. (2001) A classification based interactive algorithm of multicriteria linear integer programming. Cybernetics and Information Technologies, 1, 5–20.
[23] Genova, K., Kirilov, L. & Guljashki, V. (2013) New reference- neighbourhood scalarization problem for multiobjective integer programming. Cybernetics and Information Technologies, 13, 104–114 [DOI: 10.2478/cait-2013-0010].
[24] Gardiner, L.R. & Steuer, R.E. (1994) Unified interactive multiple objective programming: An open architecture for accommodating new procedures. Journal of the Operational Research Society, 45, 1456–1466 [DOI: 10.1057/jors.1994.222].
[25] Luque, M., Ruiz, F. & Miettinen, K. (2011) Global formulation for interactive multiobjective optimization. OR Spectrum, 33, 27–48 [DOI: 10.1007/s00291-008-0154-3].
[26] Vassileva, M., Miettinen, K. & Vassilev, V. (2005). “Generalized Scalarizing Problem for Multicriteria Optimization, IIT Working Papers IIT/WP-205. Institute of Information Technologies: Bulgaria.
[27] Narula, S., Kirilov, L. & Vassilev, V. (1992) Reference direction approach for solving multiple objective nonlinear programming problems, Xth International Conference on Multiple Criteria Decision Making, Taipei, Taiwan [Conference proceedings], vol. II, 355–362.
[28] Gardiner, L. & Vanderpooten, D. (1997) Interactive multiple criteria procedures: Some reflections. In: Multicriteria Analysis (edited by J. N. Clìimaco). Springer Verlag: Berlin, pp. 290–301.
[29] Vassilev, V.S., Narula, S.C. & Gouljashki, V.G. (2001) An interactive reference direction algorithm for solving multi-objective convex nonlinear integer programming problems. International Transactions in Operational Research, 8, 367–380 [DOI: 10.1111/ 1475-3995.00271].


Home | Aim & Scope | Editorial Board | Author Guidelines | Publisher | Subscription | Previous Issue | Contact Us |Upcoming Conferences|Sample Issues|Library Recommendation Form|

 

Copyright © 2011 dline.info