Solving in Integers Another Fractional Nonlinear Integer Programming Problem

 

Jsun Yui Wong

The computer program listed below seeks to solve the following integer problem:

Maximize ( n1x / d1x )+ (n2x / d2x )

where

n1x = X(1) ^ 2 – 4 * X(1) + 2 * X(2) ^ 2 – 8 * X(2) + 3 * X(3) ^ 2 – 12 * X(3) – 56,

n2x = 2 * X(1) ^ 2 – 16 * X(1) + X(2) ^ 2 – 8 * X(2) – 2,

d1x = X(1) ^ 2 – 2 * X(1) + X(2) ^ 2 – 2 * X(2) + X(3) + 20,

d2x = 2 * X(1) + 4 * X(2) + 6 * X(3),

subject to

X(1) + X(2) + X(3)<=10,

-X(1) – X(2) + X(3)<=4,

X(j)>=1, j=1, 2, 3,

X(1) through X(3) are integer variables.

One notes the preceding sentence, which is X(1) through X(3) are integer variables. The integer problem above is based on Example 3 in Shen, Duan, and Pei [23, p. 155].

X(4) and X(5) below are slack variables.

 

0 DEFDBL A-Z

2 DEFINT K

3 DIM B(99), N(99), A(99), H(99), L(99), U(99), X(1111), D(111), P(111), PS(33)
12 FOR JJJJ = -32000 TO 32000 STEP .01

 

14 RANDOMIZE JJJJ
16 M = -1D+37

75 A(1) = 1 + RND * 7
77 A(2) = 1 + RND * 7
1
78 A(3) = 1 + RND * 7

 

128 FOR I = 1 TO 2000

 

 

129 FOR KKQQ = 1 TO 3

130 X(KKQQ) = A(KKQQ)
131 NEXT KKQQ
133 FOR IPP = 1 TO (1 + FIX(RND * 2))

 

181 J = 1 + FIX(RND * 3)

183 r = (1 – RND * 2) * A(J)
187 X(J) = A(J) + (RND ^ (RND * 10)) * r

191 NEXT IPP
193 REM GOTO 209
196 FOR J99 = 1 TO 3

199 X(J99) = INT(X(J99))

204 NEXT J99

 

209 IF X(1) < 1 THEN 1670

212 IF X(1) > 8 THEN 1670

214 IF X(2) < 1 THEN 1670

216 IF X(2) > 8 THEN 1670
218 IF X(3) < 1 THEN 1670

222 IF X(3) > 8 THEN 1670

306 X(4) = 10 – X(1) – X(2) – X(3)

 

307 X(5) = 4 + X(1) + X(2) – X(3)
325 REM FOR J99 = 4 TO 7
326 XX(4) = X(4)
327 XX(5) = X(5)
329 IF X(4) < 0 THEN X(4) = X(4) ELSE X(4) = 0

 

330 IF X(5) < 0 THEN X(5) = X(5) ELSE X(5) = 0

331 REM NEXT J99
340 n1x = X(1) ^ 2 – 4 * X(1) + 2 * X(2) ^ 2 – 8 * X(2) + 3 * X(3) ^ 2 – 12 * X(3) – 56

 

342 n2x = 2 * X(1) ^ 2 – 16 * X(1) + X(2) ^ 2 – 8 * X(2) – 2

 

349 d1x = X(1) ^ 2 – 2 * X(1) + X(2) ^ 2 – 2 * X(2) + X(3) + 20

352 d2x = 2 * X(1) + 4 * X(2) + 6 * X(3)

 

357 POBA = n1x / d1x + n2x / d2x + 1000000 * (X(4) + X(5))

 

466 P = POBA

1111 IF P <= M THEN 1670

 

1452 M = P
1454 FOR KLX = 1 TO 5

 

1456 XXX(KLX) = XX(KLX)

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

1670 NEXT I

1889 IF M < -99999 THEN 1999

1900 PRINT A(1), A(2), A(3), A(4), A(5), XXX(4), XXX(5), M, JJJJ

1999 NEXT JJJJ

This BASIC computer program was run with qb64v1000-win [29]. The complete output through JJJJ = -31999.90000000002 is shown below:

1 2 7 0 0
0 0 -.6923076923076923 -32000

1 1 6 0 0
2 0 -1.755952380952381 -31999.99

8 1 1 0 0
0 12 -.919683257918552 -31999.98

1 1 6 0 0
2 0 -1.755952380952381 -31999.97000000001

1       8       1       0       0
0       12       -.4588235294117647       -31999.96000000001

1 1 6 0 0
2 0 -1.755952380952381 -31999.95000000001

1 1 6 0 0
2 0 -1.755952380952381 -31999.94000000001

1       8       1       0       0
0       12       -.4588235294117647       -31999.93000000001

1 1 6 0 0
2 0 -1.755952380952381 -31999.92000000001

8 1 1 0 0
0 12 -.919683257918552 -31999.91000000001

1 2 7 0 0
0 0 -.6923076923076923 -31999.90000000002

Above there is no rounding by hand; it is just straight copying by hand from the monitor screen. The candidate solution above at
JJJJ=-31999.9600000001, for example, is optimal, Shen, Duan, and Pei [23, p. 155].

On a personal computer with a Pentium Dual-Core CPU E5200 @2.50GHz, 2.50 GHz, 960 MB of RAM and qb64v1000-win [29], the wall-clock time for obtaining the output through
JJJJ= -31999.90000000002 was 2 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 Sinulation 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] Pei-Ping Shen, Yun-Peng Duan, Yong-Gang Pei. A simplicial branch and duality boundalgorithm for the sum of convex-convex ratios problem. Journal of Computational and Applied Mathematics 223 (2009) 145-158.
[24] P. B. Thanedar, G. N. Vanderplaats (1995). Survey of discrete variable optimization for structural design, Journal of Structural Engineering, 121 (2), 301-306 (1995).
[25] Jung-Fa Tsai (2005). Global optimization of nonlinear fractional programming problems in engineering design. Engineering Optimization (2005) 37:4, pp. 399-409.
[26] 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
[27] 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.
[28] 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.
[29] Wikipedia, QB64, https://en.wikipedia.org/wiki/QB64.
[30] 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/
[31] Helen Wu (2015). Geometric Programming. https://optimization.mccormick.northwstern.edu/index.php/Geometric_Programming.
[32] 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.
[33] 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.
[35] B. D. Youn, K. K. Choi (2004). A new responsesurface methodology for reliability-based design optimization. Computers and Structures 82 (2004) 241-256.