An enumerative algorithm for computing all possibly optimal solutions to an interval LP

被引:0
|
作者
Carla Oliveira
Carlos Henggeler Antunes
Carlos Barrico
机构
[1] INESC Coimbra,ISCAC Coimbra
[2] ISCAC,Departamento de Engenharia Electrotécnica e de Computadores
[3] Universidade de Coimbra Polo II,Departamento de Informática
[4] Universidade da Beira Interior,undefined
来源
TOP | 2014年 / 22卷
关键词
Interval linear programming; Optimizing approach; Possibly optimal solutions; 90C05; 90C46;
D O I
暂无
中图分类号
学科分类号
摘要
Interval programming techniques are a valuable approach for tackling uncertainty in mathematical programming models, because they only require the knowledge of the feasible range of variation of the model coefficients. Nevertheless, the use of these techniques has some limitations, namely when the number of decision variables with interval coefficients is high since the number of objective functions at stake in the sub-problem for testing the (weak) efficiency of each non-basic variable may be easily out of an acceptable computational effort. A similar problem may arise with the number of sub-problems for testing the multi-parametric optimality of each solution obtained (that is, to check whether the solution is possibly optimal or not) and the multi-parametric optimality of each edge by using the all emanating edges algorithm. An alternative algorithm is suggested that allows obtaining all possibly optimal solutions, which fulfill the formal criteria of optimality in a feasible bounded region.
引用
收藏
页码:530 / 542
页数:12
相关论文
共 50 条
  • [1] An enumerative algorithm for computing all possibly optimal solutions to an interval LP
    Oliveira, Carla
    Antunes, Carlos Henggeler
    Barrico, Carlos
    TOP, 2014, 22 (02) : 530 - 542
  • [2] Computing Possibly Optimal Solutions for Multi-Objective Constraint Optimisation with Tradeoffs
    Wilson, Nic
    Razak, Abdul
    Marinescu, Radu
    PROCEEDINGS OF THE TWENTY-FOURTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE (IJCAI), 2015, : 815 - 821
  • [3] Computing All Optimal Solutions in Satisfiability Problems with Preferences
    Di Rosa, Emanuele
    Giunchiglia, Enrico
    Maratea, Marco
    PRINCIPLES AND PRACTICE OF CONSTRAINT PROGRAMMING, 2008, 5202 : 603 - 607
  • [4] An optimal algorithm for computing all subtree repeats in trees
    Flouri, T.
    Kobert, K.
    Pissis, S. P.
    Stamatakis, A.
    PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 2014, 372 (2016):
  • [5] An algorithm for computing all solutions of an absolute value equation
    Jiri Rohn
    Optimization Letters, 2012, 6 : 851 - 856
  • [6] An algorithm for computing all solutions of an absolute value equation
    Rohn, Jiri
    OPTIMIZATION LETTERS, 2012, 6 (05) : 851 - 856
  • [7] An interval algorithm for finding all solutions of nonlinear resistive circuits
    Yamamura, K
    Igarashi, N
    Inoue, YA
    PROCEEDINGS OF THE 2003 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOL III: GENERAL & NONLINEAR CIRCUITS AND SYSTEMS, 2003, : 192 - 195
  • [8] An optimal parallel algorithm for computing cut vertices and blocks on interval graphs
    Pal, M
    Mondal, S
    Bera, D
    Pal, TK
    INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS, 2000, 75 (01) : 59 - 70
  • [9] A new algorithm for computing all solutions of an absolute value equation
    Li Jing
    Liu Jie
    Wang Meili
    Wei Fei
    2017 13TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY (CIS), 2017, : 381 - 384
  • [10] Determining Basic Variables of Optimal Solutions in Karmarkar's New LP Algorithm
    Kojima, Masakazu
    ALGORITHMICA, 1986, 1 (1-4) : 499 - 515