Solving an Integer Version of Brown’s Almost Linear System of Equations

Jsun Yui Wong

The computer program listed below seeks to solve the immediately following integer nonlinear system of equations:

2 * X(1) + X(2) + X(3) + X(4) +X(5) = 6

X(1) + 2 * X(2) + X(3) + X(4) + X(5) = 6

X(1) + X(2) + 2 * X(3) + X(4) + X(5) = 6

X(1) + X(2) + X(3) + 2 * X(4) + X(5) = 6

X(1) * X(2) * X(3) * X(4) * X(5) =1

-32<=X(i)<=32, i=1, 2, 3. 4, 5,

X(1) through X(5) are integer variables.

The problem above is based on Floudas et al.’s Test Problem 5 on p. 329 [7, Brown’s almost linear system], which is as follows

2 * X(1) + X(2) + X(3) + X(4) +X(5) = 6

X(1) + 2 * X(2) + X(3) + X(4) + X(5) = 6

X(1) + X(2) + 2 * X(3) + X(4) + X(5) = 6

X(1) + X(2) + X(3) + 2 * X(4) + X(5) = 6

X(1) * X(2) * X(3) * X(4) * X(5) =1

-2<=X(i)<=2, i=1, 2, 3. 4, 5,

X(1) through X(5) are continuous 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 31996. STEP .01

14 RANDOMIZE JJJJ

16 M = -1D+37

33 FOR J44 = 1 TO 5

34 A(J44) = -32 + RND * 64

37 NEXT J44

 

128 FOR I = 1 TO 10000

 

129 FOR KKQQ = 1 TO 5

130 X(KKQQ) = A(KKQQ)
131 NEXT KKQQ
133 FOR IPP = 1 TO (1 + FIX(RND * 3))

 

181 j = 1 + FIX(RND * 5)

189 r = (1 – RND * 2) * A(j)
190 X(j) = A(j) + (RND ^ (RND * 10)) * r

 

195 NEXT IPP

211 FOR J44 = 1 TO 5

214 X(J44) = INT(X(J44))

 

218 NEXT J44

 

225 FOR J44 = 1 TO 5

226 IF X(J44) < -32## THEN 1670

227 IF X(J44) > 32## THEN 1670
228 NEXT J44
229 GOTO 243

 

243 X(5) = -2 * X(1) – X(2) – X(3) – X(4) + 6

 

244 IF X(5) < -32## THEN 1670

245 IF X(5) > 32## THEN 1670

 

246 LHS2 = X(1) + 2 * X(2) + X(3) + X(4) + X(5) – 6
247 LHS3 = X(1) + X(2) + 2 * X(3) + X(4) + X(5) – 6

248 LHS4 = X(1) + X(2) + X(3) + 2 * X(4) + X(5) – 6
249 LHS5 = X(1) * X(2) * X(3) * X(4) * X(5) – 1

 

455 POBA = -ABS(LHS2) – ABS(LHS3) – ABS(LHS4) – ABS(LHS5)

 

466 P = POBA

1111 IF P <= M THEN 1670

 

1450 M = P
1454 FOR KLX = 1 TO 5

1455 A(KLX) = X(KLX)
1456 NEXT KLX

1557 GOTO 128

1670 NEXT I
1889 IF M < 0 THEN 1999

1907 PRINT A(1), A(2), A(3), A(4), A(5), M, JJJJ
1999 NEXT JJJJ

This BASIC computer program was run with QB64v1000-win [55]. The complete output through JJJJ = -31836.4000000262 is shown below:

1       1       1       1       1
0          -31959.75000000644

1       1       1       1       1
0          -31881.09000001903

1       1       1       1       1
0          -31836.4000000262

Above there is no rounding by hand; it is just straight copying by hand from the monitor screen. On a personal computer with a Pentium Dual-Core CPU E5200 @2.50GHz, 2.50 GHz, 960 MB of RAM and QB64v1000-win [55], the wall-clock time (not CPU time) for obtaining the output through JJJJ = -31836.4000000262 was 6 minutes, total, including the time for “Creating .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 (2002). On the posynomial fractional programming problems. European Journal of Operational Research 143 (2002) pp. 42-52.
[5] Ching-Ter Chang (2006). Formulating the mixed integer fractional posynomial programming, European Journal of Operational Research 173 (2006) pp. 370-386.

[6] Ching-Ter Chang (2017). Fuzzy linearization strategy for multiple objective linear fractional programming with binary utility functions. Computers and Industrial Engineering 112 (2017) 437-446.

[7] C. A. Floudas, P. M. Pardalos, C. S. Adjiman, W. R. Esposito, Z. H. Gumus, S. T. Harding, J. L. Klepeis, C. A. Meyer, C. A. Schweiger (1999). Handbook of Test Problems in Local and Global Optimization. Kluwer Academic Publishers 1999.

[8] Amir Hossein Gandomi, Xin-She Yang, Amir Hossein Alavi (2011). Mixed variable structural optimization using Firefly Algorithm, Computers and Structures 89 (2011) 2325-2336.
[9] 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.
[10] 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.
[11] 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.
[12] 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.

[13] E. L. Hannan (1981), Linear programming with multiple fuzzy goals, Fuzzy Sets and Systems 6 (1981) 235-246.

[14] Xue-Ping Hou, Pei-Ping Shen, Chun-Feng Wang (2014). Global Minimization for Generalized Polynomial Fractional Program. Mathmatical Problems in Engineering, Volume 2014. Hindawi Publishing Company.

[15] James P. Ignizio, Linear Programming in Single- and Multiple-Objective Systems. Prentice-Hall, Englewood Cliffs, NJ, 1982.

[16] James P. Ignizio, Stephen C. Daniels (1983). Fuzzy multicriteria integer programming via fuzzy generalized networks. Fuzzy Sets and Systems 10 (1983) 261-270.

[17] James P. Ignizio, Tom M. Cavalier, Linear Programming. Prentice-Hall, Englewood Cliffs, NJ, 1994.

[18] Majid Jaberipour, Esmaile Khorram (2010). Solving the sum of ratios problems by a harmony search algorithm. Journal of Computational and Applied Mathematics 234 (2010) 733-742.

[19] Sanjay Jain, Kailash Lachhwani (2010). Linear plus fractional multiobjective programming problem with homogeneous constraints using fuzzy approach. Iranian Journal of Operations Research, Vol. 2, No. 1, 2010, pp. 41-49.

[20] Hongwei Jiao, Zhankui Wang, Yongqiang Chen (2013). Global Optimization Algorithm for Sum of Generalized Polynomial Ratios Problems. Applied Mathematical Modelling 37 (2013) 187-197.

[21] Ali Husseinzadeh Kashan (2011). An effective algorithm for constrained global optimization and application to mechanical engineering design: League championship algorithm (LCA). Computer-Aided Design 43 (2011) 1769-1792.

[22] Ali Husseinzadeh Kashan (2015). An effective algorithm for constrained optimization based on optics inspired optimization (OIO). Computer-Aided Design 63 (2015) 52-71.

[23] K. Lachhwani (2012). Fuzzy Goal Programming Approach to Multi Objectve Quadratic Programming Problem. Proceedings of the National Academy of Sciences, India, Section A Physical Sciences (October-December 2012) 82 (4): 317-322.
https://link.springer.com/journal/40010

[24] K. Lachhwani (2014). FGP approach to multi objectve quadratic fractional programming problem. International Journal of Industrial Mathematics, vol. 6, No.1, pp. 49-57. Available online at http://ijim.srbiau.ac.ir/

[25] Han-Lin Li, Jung-Fa Tsai (2005). Treating free variables in generalized geometric global optimization programs.. Journal of Global Optimization, 33: 1-13 (2005).

[26] Han-Lin Li, Jung-Fa Tsai, Christodoulos A. Floudas (2008). Convex underestimating for posynomial functions of postive variables. Optimization Letters 2, 333-340 (2008).
[27] 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.

[28] Han-Lin Li, Hao-Chun Lu (2009). Global optimization for generalized geometric progams with mixed free-sign variables. Operations Research 57 (3): 701-713 (2009).

[29] Han-Lin Li, Hao-Chun Lu, Chia-Hui Huang, Nian-Ze Hu (2009). A superior representation method for piecewise lineat functions. INFORMS Journal on Computing 21 (2): 314-321 (2009).

[30] Han-Lin Li, Shu-Cherng Fang, Yao-Huei Huang, Tiantian Nie (2016). An enhanced logarithmic method for signomial programming with discrete variables. European Journal of Operational Research 255 (2016) pp. 922-934.
[31] Ming-Hua Lin, Jung-Fa Tsai (2011). Finding multiple optimal solutions of signomial discrete programming problems with free variables, Optimization and Engineering (2011) 12:425-443.
[32] Ming-Hua Lin, Jung-Fa Tsai (2014). A deterministic global approach for mixed-discrete structural optimization, Engineering Optimization (2014) 46:7, pp. 863-879.
[33] 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.
[34] 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.
[35] 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.

[36] Kenneth R. MacCrimmon (1973). An overview of multiple objective decision making. In James L. Cochrane, Milan Zeleny (editors), Multiple Criteria Decisiom Making. University of South Carolina Press, Columbia.
[37] 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/
[38] 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.

[39] Katta Murty, Operations Research: Deterministic Optimization Models. Prentice-Hall, 1995.

[40] 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…/
[41] Gideon Oron (1979) An algorithm for optimizing nonlinear contrained zero-one problems to improve wastewater treatment, Engineering Optimization, 4:2, 109-114.
[42] Osama Abdel Raouf, Ibraham M. Hezam (2014). Solving Fractional Programming Problems Based on Swarm Intelligence. Journal of Industrial Engineering International (2014) 10:56.

[43] 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.

[44] 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.

[45] Vikas Sharma (2012), Multobjective integer nonlinear fractional programming problem: A cutting plane approach. OPSEARCH of the Operational Research Society of India (April-June 2012) 49 (2) 133-153.

[46] 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.

[47] J. Smith (1985). Chemical Engineering Kinetics. Butterworth, Stoneham, MA.

[48] P. B. Thanedar, G. N. Vanderplaats (1995). Survey of discrete variable optimization for structural design, Journal of Structural Engineering, 121 (2), 301-306 (1995).
[49] Jung-Fa Tsai (2005). Global optimization of nonlinear fractional programming problems in engineering design. Engineering Optimization (2005) 37:4, pp. 399-409.
[50] 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
[51] 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.
[52] 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.

[53] Pei-Chun Wang, Jung-Fa Tsai, Wei-Nung Ma, Chai-Chien Lee (2010). An efficient global optimization approach for solving mixed-integer nonlinear programming problems. Proceedings of the 40th International Conference on Computers and Industrian Engineering, Japan, pp.1-4, 2010.
Date added to IEEE Xplore: 13 December 2010. Publisher:IEEE.

[54] Pei-Chun Wang, Jung-Fa Tsai (2011). Global optimization of mixed-integer nonlinear programming for engineering design problems. Proceedings of 2011 International Conference on System Science and Engineeing, Macau, China – June 2011.

[55] Wikipedia, QB64, https://en.wikipedia.org/wiki/QB64.

[56] Taeyong Yang, James P. Ignizio, and Hyun-Joon Kim, Fuzzy programming with nonlinear membership functions: Piecewise linear approximation. Fuzzy Sets and Systems 41 (1991) 39-53.
[57] H.-J. Zimmermann (1978), Fuzzy programming and linear programming with several objective functions. Fuzzy Sets and Systems 1 (1978) 45-55.