Monday, November 6, 2017

Solving a Fractional Nonlinear Integer Programming Problem


Jsun Yui Wong

The computer program listed below seeks to solve Example 4 in Chang [4, p. 383]:

Minimize 
   
 (    ABS(X(5) ^ 1.8) * X(1) * X(3) ^ .3 * X(4) ^ 1.5 + X(2) * X(3) ^ 1.8 * X(4) ^ 1.3 * X(5) + X(1) * X(2) * X(3) ^ 1.7    )  /  (    X(1) * X(3) * X(4) + X(2) * X(3) ^ 2.3 * X(4) ^ 1.4  )

subject to

         2 * X(1) + X(1) * X(3) ^ 1.6>=5,

         X(1) + X(2)>=1,

         X(2) + X(4)<=6,

         X(1) + X(2) + X(5)>=3,

        1 <=X(3)<= 7 ,

         1 <= X(4) <= 6,

         1 <= X(5) <= 5 ,

X(1) and X(2) are binary variables,

X(3) and X(4) are continuous variables,

X(5) is absolute continuous variable.


X(6) through X(9) below are slack variables.



0 DEFDBL A-Z

2 DEFINT K

3 DIM B(199), N(199), A(199), H(199), L(199), U(199), X(1111), D(111), P(111), PS(133)

12 FOR JJJJ = -32000 TO 32000 STEP .01

    14 RANDOMIZE JJJJ
    16 M = -1D+37
    71 IF RND < .5 THEN A(1) = 0 ELSE A(1) = 1

    73 IF RND < .5 THEN A(2) = 0 ELSE A(2) = 1

    84 A(3) = 1 + (RND * 7)
    85 A(4) = 1 + (RND * 6)
    86 A(5) = 1 + (RND * 5)

    128 FOR I = 1 TO 30000


        129 FOR KKQQ = 1 TO 5



            130 X(KKQQ) = A(KKQQ)
        131 NEXT KKQQ

        132 REM GOTO 162

        133 FOR IPP = 1 TO (1 + FIX(RND * 3))


            151 J = 3 + FIX(RND * 3)


            153 r = (1 - RND * 2) * A(J)
            157 X(J) = A(J) + (RND ^ (RND * 10)) * r


        161 NEXT IPP

        162 REM IF RND < .5 THEN 164
        163 REM X(1) = INT(X(1))
        164 REM IF RND < .5 THEN 197



        165 REM X(2) = INT(X(2))



        197 IF X(3) < 1 THEN 1670

        199 IF X(3) > 7 THEN 1670

        201 IF X(4) < 1 THEN 1670

        203 IF X(4) > 6 THEN 1670


        205 IF X(5) < 1 THEN 1670

        207 IF X(5) > 5 THEN 1670

        261 X(6) = -5 + 2 * X(1) + X(1) * X(3) ^ 1.6


        264 X(7) = -1 + X(1) + X(2)

        267 X(8) = 6 - X(2) - X(4)

        269 X(9) = -3 + X(1) + X(2) + X(5)



        281 FOR J99 = 6 TO 9

            283 IF X(J99) < 0 THEN X(J99) = X(J99) ELSE X(J99) = 0


        285 NEXT J99

        311 ups = ABS(X(5) ^ 1.8) * X(1) * X(3) ^ .3 * X(4) ^ 1.5 + X(2) * X(3) ^ 1.8 * X(4) ^ 1.3 * X(5) + X(1) * X(2) * X(3) ^ 1.7

        322 dow = X(1) * X(3) * X(4) + X(2) * X(3) ^ 2.3 * X(4) ^ 1.4


        365 POBA = -ups / dow + 1000000 * (X(6) + X(7) + X(8) + X(9))


        466 P = POBA

        1111 IF P <= M THEN 1670


        1452 M = P
        1454 FOR KLX = 1 TO 9



            1459 A(KLX) = X(KLX)
        1460 NEXT KLX
        1557 REM  GOTO 128

    1670 NEXT I


    1777 FOR J44 = 6 TO 9

        1778 IF A(J44) < 0 THEN 1999
    1779 NEXT J44

    1889 IF M < -.5 THEN 1999


    1908 PRINT A(1), A(2), A(3), A(4), A(5), A(6), A(7), A(8), A(9), M, JJJJ

1999 NEXT JJJJ


This BASIC computer program was run with qb64v1000-win [28]. The complete output through JJJJ =  -31999.88000000002 is  shown below:

1      1      6.999999999990646      4.9999999999972
1.000000000004951      0      0      0
0      -.3632313212606416      -31999.96000000001

1      1      6.99999999999997       4.999999999991044
1.000000000003382      0      0      0
0      -.3632313212599075      -31999.90000000002

1      1      6.9999999999965         4.99999999999999
1.000000000001283      0      0      0
0      -.3632313212591524      -31999.88000000002

Above there is no rounding by hand; it is just straight copying by hand from the monitor screen.  The computational results above can be compared with the results in Chang [4, p. 385].

On a personal computer with a Pentium Dual-Core CPU E5200 @2.50GHz, 2.50 GHz, 960 MB of RAM and qb64v1000-win [28], the wall-clock time for obtaining the output through JJJJ=   -31999.88000000002 was 3 seconds, not including the time for creating the .EXE file.   
   

Acknowledgment

I would like to acknowledge the encouragement of Roberta Clark and Tom Clark.

References

[1] Yuichiro Anzai (1974). On Integer Fractional Programming. Journal of the Operations Research Society of Japan, Volume 17, No. 1, March 1974, pp. 49-66.  http://www..orsj.or.jp/~archiv/pdf/e_mag/Vol.17_01_049.pdf.
[2] Sjirk Boon. Solving systems of nonlinear equations. Sci. Math. Num-Analysis,1992, Newsgroup Article 3529.
[3]  S. S. Chadha (2002).   Fractional programming with absolute-value functions.   European Journal of Operational Research 141 (2002) pp. 233-238.
[4]  Ching-Ter Chang (2006).   Formulating the mixed integer fractional posynomial programming,  European Journal of Operational Research 173 (2006) pp. 370-386.       
[5] Piya Chootinan, Anthony Chen (2006). Constraint Handling in genetic algorithms using a gradient-based repair method. Computers and Operations Research 33 (2006) 2263-2281.
[6] Amir Hossein Gandomi, Xin-She Yang, Amir Hossein Alavi (2011). Mixed variable structural optimization using Firefly Algorithm, Computers and Structures 89 (2011) 2325-2336.
[7] Amir Hossein Gandomi, Xin-She Yang, Siamak Taratahari, Amir Hossein Alavi (2013). Firefly Algorithm with Chaos, Communications in Nonlinear Science and Numerical Simulation 18 (2013) 89-98.
[8] Amir Hossein Gandomi, Xin-She Yang, Amir Hossein Alavi (2013). Cuckoo search algorithm: a metaheuristicapproach to solve structural optimization problem. Engineering with Computers (2013) 29:17-35.
[9] Amir Hossein Gandomi, Xin-She Yang, Amir Hossein Alavi (2013). Erratum to: Cuckoo search algorithm: a metaheuristicapproach to solve structural optimization problem. Engineering with Computers (2013) 29:245.
[10]  Chrysanthos E. Gounaris, Christodoulos A. Floudas.  Tight convex underestimators for Csquare-continuous problems: II. multivariate functions.  Journal of Global Optimization (2008) 42, pp. 69-89.

[11]  Han-Lin Li, Jung-Fa Tsai, Christodoulos A. Floudas (2008).  Convex underestimating for posynomial functions of postive variables.  Optimization Letters 2, 333-340 (2008).
[12] Han-Lin Li, Jung-Fa Tsai (2008). A distributed computational algorithm for solving portfolio problems with integer variables. European Journal of Operational Research 186 (2008) pp. 882-891.
[13] Ming-Hua Lin, Jung-Fa Tsai (2014). A deterministic global approach for mixed-discrete structural optimization, Engineering Optimization (2014) 46:7, pp. 863-879.
[14]  Hao-Chun Lu, Han-Lin Li, Chrysanthos E. Gounaris, Christodoulos A. Floudas (2010).  Convex relaxation for solving posynomial problems.  Journal of Global Optimization (2010) 46, pp. 147-154.
[15]  Hao-Chun Lu (2012).  An efficient convexification method for solving generalized geometric problems.  Journal of Industrial and Management Optimization, Volume 8, Number 2, May 2012, pp. 429-455.
[16]  Hao-Chun Lu (2017).  Improved logarithnic linearizing method for optimization problems with free-sign pure discrete signomial terms. Journal of Global Optimization (2017) 68, pp. 95-123.
[17] Mathworks. Solving a mixed integer engineering design problem using the genetic algorithm – MATLAB & Simulink Example.
https://www.mathworks.com/help/gads/examples/solving-a-mixed-integer-engineering-design-problem-using-the-genetic-algorithm.html/
[18] Microsoft Corp., BASIC, Second Edition (May 1982), Version 1.10. Boca Raton, Florida: IBM Corp., Personal Computer, P. O. Box 1328-C, Boca Raton, Florida 33432, 1981.
[19] Sinan Melih Nigdeli, Gebrail Bekdas, Xin-She Yang (2016). Application of the Flower Pollination Algoritm in Structural Engineering. Springer International Publishing Switzerland 2016. http://www.springer.com/cda/content/document/cda…/
[20] Gideon Oron (1979) An algorithm for optimizing nonlinear contrained zero-one problems to improve wastewater treatment, Engineering Optimization, 4:2, 109-114.
[21] H. S. Ryoo, N. V. Sahinidis (1995). Global optimization of nonconvex NLP and MINLP with applications in process design. Computers and Chemical Engineering Vol. 19 (5) (1995) pp. 551-566.
[22] c. R. Seshan, V. G. Tikekar (1980) Algorithms for Fractional Programming. Journal of the Indian Institute of Science 62 (B), Feb. 1980, Pp. 9-16.
[23] P. B. Thanedar, G. N. Vanderplaats (1995). Survey of discrete variable optimization for structural design, Journal of Structural Engineering, 121 (2), 301-306 (1995).
[24] Jung-Fa Tsai (2005). Global optimization of nonlinear fractional programming problems in engineering design. Engineering Optimization (2005) 37:4, pp. 399-409.
[25] Jung-Fa Tsai, Ming-Hua Lin (2007). Finding all solutions of systems of nonlinear equations with free variables. Engineering Optimization (2007) 39:6, pp. 649-659
[26] Jung-Fa Tsai, Ming-Hua Lin, Yi-Chung Hu (2007). On generalized geometric programming problems with non-positive variables. European Journal of Operational Research 178 (2007) pp. 10-19.
[27] Jung-Fa Tsai, Ming-Hua Lin (2008). Global optimization of signomial mixed-integer nonlinear programming with free variables. Journal of Global Optimization (2008) 42 pp. 39-49.
[28] Wikipedia, QB64, https://en.wikipedia.org/wiki/QB64.
[29] Jsun Yui Wong (2012, April 12). The Domino Method of General Integer Nonlinear Programming Applied to a Nonlinear Fractional Programming Problem from the Literature. http://myblogsubstance.typepad.com/substance/2012/04/12/
[30]  Helen Wu (2015).  Geometric Programming.  https://optimization.mccormick.northwstern.edu/index.php/Geometric_Programming.
[31] Xin-She Yang, Christian Huyck, Mehmet Karamanoglu, Nawaz Khan (2014). True global optimality of the pressure vessel design problem: A benchmark for bio-inspired optimisation algorithms.  https://arxiv.org/pdf/1403.7793.pdf.
[32] Xin-She Yang, Amir Hossein Gandomi (2012). Bat algorithm: a novel approach for global engineering optimization. Engineering Computations: International Journal for Computer-Aided Engineering and Software, Vol. 20,No. 5, 2012, pp. 461-483.
[33] B. D. Youn, K. K. Choi (2004). A new responsesurface methodology for reliability-based design optimization.  Computers and Structures 82 (2004) 241-256.

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