A computer program for solving mixed-integer nonllnear programs

A computer program for solving mixed-integer nonllnear programs
Jsun Yui Wong
Similar to the computer program of the preceding paper, the computer program listed below aims to solve the following nonlinear program from Tsai and Lin [89, p. 47, Example 2]:
Minimize
X(1) ^ .5 * X(2) + 3 * LOG(X(1))
subject to
-X(1) + X(2) <= 5
X(1) ^ .5 – X(2) <= 6
X(1) epsilon {0.1, 0.5, 0.7, 1.2}
-6 <= X(2) <= 4.

One notes that X(1) is a discrete variable, and X(2) is a free variable.

0 REM DEFDBL A-Z
1 REM DEFINT I, J, K
2 REM DIM B(99), N(99), A(2002), H(99), L(99), U(99), X(2002), D(111), P(111), PS(33), J(99), AA(99), HR(32), HHR(32), LHS(44), PLHS(44), LB(22), UB(22), PX(44), J44(44), PN(22), NN(22)
85 FOR JJJJ = -32000 TO 32000

89 RANDOMIZE JJJJ
90 M = -3D+30
111 IF RND < .25 THEN A(1) = .1 ELSE IF RND < .3333 THEN A(1) = .5 ELSE IF RND < .5 THEN A(1) = .7 ELSE A(1) = 1.2

112 A(2) = -6 + RND * 10


128 FOR i = 1 TO 20000

    129 FOR KKQQ = 1 TO 2

        130 X(KKQQ) = A(KKQQ)

    131 NEXT KKQQ

    139 FOR IPP = 1 TO FIX(1 + RND * 2)


        141 B = 1 + FIX(RND * 2)

        144 REM  IF RND < .9999 THEN 160 ELSE GOTO 167
        147 IF B = 2 THEN 160 ELSE GOTO 167


        160 r = (1 - RND * 2) * A(B)

        164 X(B) = A(B) + (RND ^ (RND * 15)) * r

        165 GOTO 168

        166 REM   IF RND < .5 THEN X(B) = A(B) - FIX(RND * 2) ELSE X(B) = A(B) + FIX(RND * 2)



        167 IF RND < .25 THEN X(1) = .1 ELSE IF RND < .3333 THEN X(1) = .5 ELSE IF RND < .5 THEN X(1) = .7 ELSE X(1) = 1.2



    168 NEXT IPP
    177 REM     X(3) = INT(X(3))
    181 IF -X(1) + X(2) > 5 THEN 1670



    184 IF X(1) ^ .5 - X(2) > 6 THEN 1670

    324 IF X(1) > 1.2 THEN 1670

    325 IF X(1) < .1 THEN 1670

    343 IF X(2) > 4 THEN 1670
    345 IF X(2) < -6 THEN 1670
    441 PD1 = -X(1) ^ .5 * X(2) - 3 * LOG(X(1))
    469 P = PD1

    1111 IF P <= M THEN 1670

    1452 M = P

    1454 FOR KLX = 1 TO 2
        1455 A(KLX) = X(KLX)

    1459 NEXT KLX

1670 NEXT i
1777 IF M < -999999 THEN 1999


1888 PRINT A(1), A(2), M, JJJJ

1999 NEXT JJJJ

This computer program was run with qb64v1000-win [102]. Its complete output of one run through JJJJ= -31995 is shown below:

.1 -5.683772 8.705122 -32000
.1 -5.683772 8.705122 -31999

.1 1.667091E-07 6.907755 -31998
.1 -5.683772 8.705122 -31997
.1 -5.683772 8.705122 -31996
.1 -5.683772 8.705122 -31995

Above there is no rounding by hand; it is just straight copying by hand from the monitor screen. By using the following computer system and QB64v1000-win [102], the wall-clock time (not CPU time) for obtaining the output through JJJJ = -31995 was 2 seconds, counting from “Starting program…”. One can compare the computational results above with those in Tsai and Lin [89, p. 47; Table 1 on p. 47].
The computational results presented above were obtained from the following computer system:
Processor: Intel (R) Core (TM) i5 CPU M 430 @2.27 GHz 2.26 GHz
Installed memory (RAM): 4.00GB (3.87 GB usable)
System type: 64-bit Operating System.

Acknowledgement
I would like to acknowledge the encouragement of Roberta Clark and Tom Clark.
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A computer program for solving mixed-integer nonlinear programs with/without free variables

A computer program for solving mixed-integer nonlinear programs with/without free variables


Jsun Yui Wong


Similar to the computer program of the preceding paper, the computer program listed below aims to solve the following signomial mixed-integer nonlinear programming problem with a free variable from Tsai and Lin [89, p. 45, Example 1].


Minimize


-1 * ( -X(1) ^ 2 * X(2) ^ -2 * X(3) + 2 * X(2) ^ .7 * X(3) ^ .2 – X(4) * X(5) ^ -2 + 2 * X(1) + 4 * X(3) )


subject to


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

    X(3) ^ 1.5 * X(4) + .5 * X(2) + 3 * X(1) <= -10 

    -X(1) - .5 * X(4) + X(5) <= 6 

-7 <= X(1) <= 5
1 <= X(2) <= 10
1 <= X(3) <= 5
2 <= X(4) <= 8
2 <= X(5) <= 9
X(1), X(2),X(4),X(5) epsilon R
X(3) epsilon Z.


One notes that X(1) is a free variable, and X(3) is an integer variable.

0 REM DEFDBL A-Z
1 REM DEFINT I, J, K
2 REM DIM B(99), N(99), A(2002), H(99), L(99), U(99), X(2002), D(111), P(111), PS(33), J(99), AA(99), HR(32), HHR(32), LHS(44), PLHS(44), LB(22), UB(22), PX(44), J44(44), PN(22), NN(22)
85 FOR JJJJ = -32000 TO 32000

89 RANDOMIZE JJJJ
90 M = -3D+30
92 REM     FOR J44 = 1 TO 3

94 REM  IF RND < .25 THEN A(1) = .1 ELSE IF RND < .333 THEN A(1) = .5 ELSE IF RND < .5 THEN A(1) = .7 ELSE A(1) = 1.2
99 A(1) = -7 + RND * 12
111 A(2) = 1 + RND * 9
113 A(3) = 1 + RND * 4
115 A(4) = 2 + RND * 6
117 A(5) = 2 + RND * 7

128 FOR i = 1 TO 200000




    129 FOR KKQQ = 1 TO 5

        130 X(KKQQ) = A(KKQQ)

    131 NEXT KKQQ

    139 FOR IPP = 1 TO FIX(1 + RND * 5)


        141 B = 1 + FIX(RND * 5)

        144 IF RND < .9999 THEN 160 ELSE GOTO 167

        160 r = (1 - RND * 2) * A(B)

        164 X(B) = A(B) + (RND ^ (RND * 15)) * r

        165 GOTO 168

        167 REM   IF RND < .5 THEN X(B) = A(B) - FIX(RND * 2) ELSE X(B) = A(B) + FIX(RND * 2)

    168 NEXT IPP
    176 REM  FOR J44 = 1 TO 4

    177 X(3) = INT(X(3))

    180 REM  NEXT J44
    181 IF X(1) + 6 * X(2) - X(3) - 5 * X(4) > 2 THEN 1670


    182 IF X(3) ^ 1.5 * X(4) + .5 * X(2) + 3 * X(1) > -10 THEN 1670

    183 REM  X(2) = 8 - 2 * X(1) - X(3)


    184 IF -X(1) - .5 * X(4) + X(5) > 6 THEN 1670

    188 REM IF X(1) + 2 * X(3) > 10 THEN 1670
    222 REM    IF 8 * X(1) ^ 3 - 2 * X(1) ^ 4 - 8 * X(1) ^ 2 + X(2) > 2 THEN 1670

    229 REM  IF 32 * X(1) ^ 3 - 4 * X(1) ^ 4 - 88 * X(1) ^ 2 + 96 * X(1) + X(2) > 36 THEN 1670

    324 IF X(1) > 5 THEN 1670

    325 IF X(1) < -7 THEN 1670
    327 REM    IF X(1) < .099999 THEN 1670


    343 IF X(2) > 10 THEN 1670

    345 IF X(2) < 1 THEN 1670
    347 IF X(3) > 5 THEN 1670

    349 IF X(3) < 1 THEN 1670
    357 IF X(4) > 8 THEN 1670

    359 IF X(4) < 2 THEN 1670
    367 IF X(5) > 9 THEN 1670

    369 IF X(5) < 2 THEN 1670

    468 PD1 = -X(1) ^ 2 * X(2) ^ -2 * X(3) + 2 * X(2) ^ .7 * X(3) ^ .2 - X(4) * X(5) ^ -2 + 2 * X(1) + 4 * X(3)

    469 P = PD1

    1111 IF P <= M THEN 1670

    1452 M = P

    1454 FOR KLX = 1 TO 5
        1455 A(KLX) = X(KLX)

    1459 NEXT KLX

1670 NEXT i
1777 IF M < -2.906 THEN 1999

1888 PRINT A(1), A(2), A(3), A(4), A(5), M, JJJJ

1999 NEXT JJJJ

This computer program was run with qb64v1000-win [102]. Its complete output of one run through JJJJ= -31798 is shown below:

-5.372923 4.584325 1 3.826606 2.54038
-2.905813 -31987


-5.349777 4.540757 1 3.778953 2.539699
-2.905586 -31963


-5.335738 4.514329 1 3.750048 2.539286
-2.905672 -31798


Above there is no rounding by hand; it is just straight copying by hand from the monitor screen. By using the following computer system and QB64v1000-win [102], the wall-clock time (not CPU time) for obtaining the output through JJJJ = -31798 was 3 minutes, counting from “Starting program…”. One can compare the computational results above with those in Tsai and Lin [89, p. 46; Table 1 on p. 47].


The computational results presented above were obtained from the following computer system:
Processor: Intel (R) Core (TM) i5 CPU M 430 @2.27 GHz 2.26 GHz
Installed memory (RAM): 4.00GB (3.87 GB usable)
System type: 64-bit Operating System.

Acknowledgement
I would like to acknowledge the encouragement of Roberta Clark and Tom Clark.
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A Computer Program for a Chemical Equilibrium Problem

A Computer Program for a Chemical Equilibrium Problem


Jsun Yui Wong


Similar to the computer program of the preceding paper, the computer program listed below aims to solve directly the following nonlinear programming problem from Bracken and McCormick [15, p. 48]:

Minimize


T1+ … + T10
where T1 = X(1) * (-6.089 + LOG(X(1) / S)), . .., T10 = X(10) * (-22.179 + LOG(X(10) / S)),
where S = X(1) + X(2) + X(3) + X(4) + X(5) + X(6) + X(7) + X(8) + X(9) + X(10)


subject to


X(1) + 2 * X(2) + 2 * X(3) + X(6) + X(10) =2
X(4) + 2 * X(5) + X(6) + X(7) =1
X(3) + X(7) + X(8) + 2 * X(9) + X(10) =1
X(1)>=0,…, X(10)>=0.

0 REM DEFDBL A-Z
1 REM DEFINT I, J, K
2 DIM B(99), N(99), A(2002), H(99), L(99), U(99), X(2002), D(111), P(111), PS(33), J(99), AA(99), HR(32), HHR(32), LHS(44), PLHS(44), LB(22), UB(22), PX(44), J44(44), PN(22), NN(22)
85 FOR JJJJ = -32000 TO 32000

89 RANDOMIZE JJJJ
90 M = -3D+30

92 FOR J44 = 1 TO 10

    93 A(J44) = .0001 + RND

94 NEXT J44

128 FOR i = 1 TO 30000

    129 FOR KKQQ = 1 TO 10

        130 X(KKQQ) = A(KKQQ)

    131 NEXT KKQQ

    139 FOR IPP = 1 TO FIX(1 + RND * 7)
        141 B = 1 + FIX(RND * 10)

        144 IF RND < .5 THEN 160 ELSE GOTO 167

        160 r = (1 - RND * 2) * A(B)

        164 X(B) = A(B) + (RND ^ (RND * 15)) * r

        165 GOTO 168

        167 REM   IF RND < .5 THEN X(B) = A(B) - FIX(RND * 2) ELSE X(B) = A(B) + FIX(RND * 2)

    168 NEXT IPP

    281 X(7) = 1 - X(4) - 2 * X(5) - X(6)


    284 X(1) = 2 - 2 * X(2) - 2 * X(3) - X(6) - X(10)
    288 X(8) = 1 - X(3) - X(7) - 2 * X(9) - X(10)


    311 FOR J44 = 1 TO 10
        321 IF X(J44) < 0 THEN 1670

        322 IF X(J44) > 10 THEN 1670
    331 NEXT J44
    447 S = X(1) + X(2) + X(3) + X(4) + X(5) + X(6) + X(7) + X(8) + X(9) + X(10)

    451 T1 = X(1) * (-6.089 + LOG(X(1) / S))
    452 T2 = X(2) * (-17.164 + LOG(X(2) / S))
    453 T3 = X(3) * (-34.054 + LOG(X(3) / S))
    454 T4 = X(4) * (-5.914 + LOG(X(4) / S))
    455 T5 = X(5) * (-24.721 + LOG(X(5) / S))
    456 T6 = X(6) * (-14.986 + LOG(X(6) / S))
    457 T7 = X(7) * (-24.100 + LOG(X(7) / S))
    458 T8 = X(8) * (-10.708 + LOG(X(8) / S))
    459 T9 = X(9) * (-26.662 + LOG(X(9) / S))
    460 T10 = X(10) * (-22.179 + LOG(X(10) / S))

    464 PD1 = -T1 - T2 - T3 - T4 - T5 - T6 - T7 - T8 - T9 - T10

    466 P = PD1

    1111 IF P <= M THEN 1670

    1452 M = P

    1454 FOR KLX = 0 TO 10


        1455 A(KLX) = X(KLX)

    1456 NEXT KLX

1670 NEXT i

1777 IF M < -47.77 THEN 1999
1888 PRINT A(1), A(2), A(3), A(4), A(5), A(6), A(7), A(8), A(9), A(10), M, JJJJ

1999 NEXT JJJJ

This computer program was run with qb64v1000-win [102]. Its complete output of one run through JJJJ= -31972 is shown below:

4.083138E-02 .1497418 .7803211 1.408125E-03
.4850834 6.988918E-04 2.772626E-02
1.817354E-02 3.771763E-02 9.834383E-02
47.76106 -31990

4.079816E-02 .1529855 .7762265 1.414638E-03
.4849713 7.259846E-04 2.791685E-02
.0182576 3.877413E-02 .1000517 47.76088
-31972

Above there is no rounding by hand; it is just straight copying by hand from the monitor screen. By using the following computer system and QB64v1000-win [102], the wall-clock time (not CPU time) for obtaining the output through JJJJ = -31972 was 3 seconds, counting from “Starting program…”. One can compare the computational results above with those in Bracken and McCormick [15, p. 49, Table 5.2].


The computational results presented above were obtained from the following computer system:
Processor: Intel (R) Core (TM) i5 CPU M 430 @2.27 GHz 2.26 GHz
Installed memory (RAM): 4.00GB (3.87 GB usable)
System type: 64-bit Operating System.

Acknowledgement
I would like to acknowledge the encouragement of Roberta Clark and Tom Clark.
References
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A Computer Program for Solving Signomial Programs

A Computer Program for Solving Signomial Programs


Jsun Yui Wong


Similar to the computer program of the preceding paper, the computer program listed below aims to solve the following nonlinear programming problem in Yan [106, pp. 60-61, Problem A]:

Minimize


-1 * ( -3 * X(1) ^ 2 – 2 * X(2) ^ 2 – X(3) ^ 2 – X(4) ^ 2 – 7 * X(1) – 565 + 39 * X(2) + 17 * X(3) + X(4) )


subject to


(1 / 6) * X(1) ^ 2 + (1 / 18) * X(2) ^ 2 + (1 / 9) * X(4) ^ 2 + (1 / 18) * X(1) – (1 / 9) * X(3) ^ 2 – (1 / 18) * X(2) <= 1
X(1) ^ 2 + X(3) ^ 2 + 2.5 * X(4) ^ 2 + X(3) + 9.5 – 4 * X(2) ^ 2 – X(4) <= 1
X(2) ^ 2 + 3 * X(3) ^ 2 + X(4) ^ 2 + X(2) – X(2) ^ 2 – X(1) – X(4) – 2 <= 1
.01 <= X(i) <= 10, i=1, 2, 3, 4.

0 REM DEFDBL A-Z
1 REM DEFINT I, J, K
2 DIM B(99), N(99), A(2002), H(99), L(99), U(99), X(2002), D(111), P(111), PS(33), J(99), AA(99), HR(32), HHR(32), LHS(44), PLHS(44), LB(22), UB(22), PX(44), J44(44), PN(22), NN(22)
85 FOR JJJJ = -32000 TO 32000
89 RANDOMIZE JJJJ
90 M = -3D+30
92 FOR J44 = 1 TO 4
93 A(J44) = .01 + RND * 9.99

94 NEXT J44

128 FOR i = 1 TO 50000
    129 FOR KKQQ = 1 TO 4

        130 X(KKQQ) = A(KKQQ)

    131 NEXT KKQQ

    139 FOR IPP = 1 TO FIX(1 + RND * 4)
        141 B = 1 + FIX(RND * 4)

        144 IF RND < .5 THEN 160 ELSE GOTO 167

        160 r = (1 - RND * 2) * A(B)

        164 X(B) = A(B) + (RND ^ (RND * 15)) * r

        165 GOTO 168

        167 REM   IF RND < .5 THEN X(B) = A(B) - FIX(RND * 2) ELSE X(B) = A(B) + FIX(RND * 2)

    168 NEXT IPP

   244 X(1) = X(2) ^ 2 + 3 * X(3) ^ 2 + X(4) ^ 2 + X(2) - X(2) ^ 2 - X(4) - 2 - 1

    298 IF X(1) ^ 2 + X(3) ^ 2 + 2.5 * X(4) ^ 2 + X(3) + 9.5 - 4 * X(2) ^ 2 - X(4) > 1 THEN 1670

    300 IF (1 / 6) * X(1) ^ 2 + (1 / 18) * X(2) ^ 2 + (1 / 9) * X(4) ^ 2 + (1 / 18) * X(1) - (1 / 9) * X(3) ^ 2 - (1 / 18) * X(2) > 1 THEN 1670

    320 FOR J44 = 1 TO 4

        322 IF X(J44) > 10 THEN 1670

        325 IF X(J44) < .01 THEN 1670

    328 NEXT J44

    464 PD1 = -3 * X(1) ^ 2 - 2 * X(2) ^ 2 - X(3) ^ 2 - X(4) ^ 2 - 7 * X(1) - 565 + 39 * X(2) + 17 * X(3) + X(4)

    466 P = PD1

    1111 IF P <= M THEN 1670

    1452 M = P

    1454 FOR KLX = 1 TO 4

        1455 A(KLX) = X(KLX)
        1457 LHSS = LHS

    1459 NEXT KLX

1670 NEXT i

1777 IF M < -443.9167 THEN 1999
1888 PRINT A(1), A(2), A(3), A(4), M, JJJJ

1999 NEXT JJJJ

This computer program was run with qb64v1000-win [102]. Its complete output of one run through JJJJ= -31802 is shown below:


1.027723 4.197347 .1625673 .4669557 -443.9155
-31839


1.025339 4.197794 .1600394 .4734082 -443.916
-31816


1.027303 4.196894 .1628246 .4704335 -443.9155
-31802

Above there is no rounding by hand; it is just straight copying by hand from thera monitor screen. By using the following computer system and QB64v1000-win [102], the wall-clock time (not CPU time) for obtaining the output through JJJJ = -31802 was 18 seconds, counting from “Starting program…”. One can compare the computational results above with those in Yan [106, p. 64].


The computational results presented above were obtained from the following computer system:
Processor: Intel (R) Core (TM) i5 CPU M 430 @2.27 GHz 2.26 GHz
Installed memory (RAM): 4.00GB (3.87 GB usable)
System type: 64-bit Operating System.

Acknowledgement
I would like to acknowledge the encouragement of Roberta Clark and Tom Clark.
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A Computer Program for Designing a Heat Exchanger Network

A Computer Program for Designing a Heat Exchanger Network


Jsun Yui Wong


Similar to the computer program of the preceding paper, the computer program listed below aims to solve the following nonlinear programming reformulation from an eight-variable problem to a five-variable problem in Babu and Angira [10, p. 994]:

Minimize


X(1) + X(2) + X(3)


subject to


833.33252 * X(4) + 100 * X(1) – X(1) * (400 – X(4)) – 83333.333 <= 0
-1250 * X(4) + 1250 * X(5) + X(2) * X(4) – X(2) * (400 – X(5) + X(4)) <= 0
-2500 * X(5) + X(3) * X(5) – X(3) * (100 + X(5)) + 1250000 <= 0
100<= X(1) <= 10000
1000<= X(2), X(3) <= 10000
10 <= X(4), X(5) <= 1000.

0 REM DEFDBL A-Z
1 REM DEFINT I, J, K
2 DIM B(99), N(99), A(2002), H(99), L(99), U(99), X(2002), D(111), P(111), PS(33), J(99), AA(99), HR(32), HHR(32), LHS(44), PLHS(44), LB(22), UB(22), PX(44), J44(44), PN(22), NN(22)
85 FOR JJJJ = -32000 TO 32000
89 RANDOMIZE JJJJ
90 M = -3D+30
91 A(1) = 100 + RND * 9900
92 FOR J44 = 2 TO 3
93 A(J44) = 1000 + RND * 9000

94 NEXT J44

113 FOR J44 = 4 TO 5
    114 A(J44) = 10 + RND * 990

115 NEXT J44

128 FOR i = 1 TO 50000

    129 FOR KKQQ = 1 TO 5


        130 X(KKQQ) = A(KKQQ)

    131 NEXT KKQQ

    139 FOR IPP = 1 TO FIX(1 + RND * 5)


        141 B = 1 + FIX(RND * 5)


        144 IF RND < .5 THEN 160 ELSE GOTO 167

        160 r = (1 - RND * 2) * A(B)

        164 X(B) = A(B) + (RND ^ (RND * 15)) * r

        165 GOTO 168

        167 REM    IF RND < .5 THEN X(B) = A(B) - FIX(RND * 10) ELSE X(B) = A(B) + FIX(RND * 10)

    168 NEXT IPP

    211 IF 833.33252 * X(4) + 100 * X(1) - X(1) * (400 - X(4)) - 83333.333 > 0 THEN 1670

    309 IF -1250 * X(4) + 1250 * X(5) + X(2) * X(4) - X(2) * (400 - X(5) + X(4)) > 0 THEN 1670

    310 IF -2500 * X(5) + X(3) * X(5) - X(3) * (100 + X(5)) + 1250000 > 0 THEN 1670

    321 FOR J44 = 4 TO 5


        322 IF X(J44) > 1000 THEN 1670

        325 IF X(J44) < 10 THEN 1670

    328 NEXT J44


    340 FOR J44 = 2 TO 3

        342 IF X(J44) > 10000 THEN 1670

        345 IF X(J44) < 1000 THEN 1670

    348 NEXT J44

    387 IF X(1) > 10000 THEN 1670

    389 IF X(1) < 100 THEN 1670

    464 PD1 = (-X(1) - X(2) - X(3))

    466 P = PD1

    1111 IF P <= M THEN 1670

    1452 M = P

    1454 FOR KLX = 1 TO 5

        1455 A(KLX) = X(KLX)

    1459 NEXT KLX

1670 NEXT i

1777 IF M < -7055 THEN 1999
1888 PRINT A(1), A(2), A(3), A(4), A(5), M, JJJJ

1999 NEXT JJJJ

This computer program was run with qb64v1000-win [102]. Its complete output of one run through JJJJ= -31191 is shown below:

523.2886 1332.708 5196.468 177.1459 292.1413
-7052.465 -31960

592.5374 1362.049 5094.798 183.1124 296.2081
-7049.384 -31191

Above there is no rounding by hand; it is just straight copying by hand from thera monitor screen. By using the following computer system and QB64v1000-win [102], the wall-clock time (not CPU time) for obtaining the output through JJJJ = -31191 was 48 seconds, counting from “Starting program…”. One can compare the computational results above with those in Babu and Angira [10, p. 994] and in Yan [106, p. 65].


The computational results presented above were obtained from the following computer system:
Processor: Intel (R) Core (TM) i5 CPU M 430 @2.27 GHz 2.26 GHz
Installed memory (RAM): 4.00GB (3.87 GB usable)
System type: 64-bit Operating System.

Acknowledgement
I would like to acknowledge the encouragement of Roberta Clark and Tom Clark.
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“What If …” And Discrete Variables To Help Solve Nonlinear Programming Problems: An Illustration

“What If…” and Discrete Variables To Help Solve Nonlinear Programming Problems: Another Illustration

Jsun Yui Wong

Similar to the computer program of the preceding paper, the computer program listed below seeks to solve the following mathematical formulation in Wang, Zhang, and Gao [99, p. 1514, Example 6], which is as follows:

Minimize

     X(3) ^ .8 * X(4) ^ 1.2

subject to

         X(1)*X(4) ^ -1  + X(2) ^ -1 * X(4) ^ -1 <= 1

        -X(1) ^ -2 * X(3) ^ -1 – X(2) * X(3) ^ -1 <= -1

.1 <= X(1) <= 1

5<= X(2) <= 10

8<= X(3) <= 15

.01 <= X(4) <= 1.

0 REM DEFDBL A-Z

1 REM DEFINT I, J, K                                                            

2 DIM B(99), N(99), A(200), H(99), L(99), U(99), X(200), D(111), P(111), PS(33), J(99), AA(99), HR(32), HHR(32), LHS(44), PLHS(44), LB(22), UB(22), PX(44), J44(44), PN(22), NN(22)

79 FOR JJJJ = -32000 TO 32000 STEP .1

    89 RANDOMIZE JJJJ

    90 M = -3D+30

    95 A(1) = INT(100 * (.1 + RND * .9)) / 100

    97 A(2) = INT(100 * (5 + RND * 5)) / 100

    98 A(3) = INT(100 * (8 + RND * 7)) / 100

    99 A(4) = INT(100 * (.01 + RND * .99)) / 100

    123 FOR I = 1 TO 5000

        129 FOR KKQQ = 1 TO 4

            130 X(KKQQ) = A(KKQQ)

        131 NEXT KKQQ

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

            140 B = 1 + FIX(RND * 4)

            144 IF RND < .5 THEN 160 ELSE GOTO 166

            160 r = (1 – RND * 2) * A(B)

            164 X(B) = A(B) + FIX((RND ^ (RND * 15)) * r)

            165 GOTO 168

            166 IF RND < .5 THEN X(B) = A(B) – FIX(RND * 2) ELSE X(B) = A(B) + FIX(RND * 2)

        168 NEXT IPP

        191 IF X(1) < .1 THEN 1670

        192 IF X(1) > 1 THEN 1670

        193 IF X(2) < 5 THEN 1670

        194 IF X(2) > 10 THEN 1670

        200 IF X(3) < 8 THEN 1670

        201 IF X(3) > 15 THEN 1670

        202 IF X(4) < .01 THEN 1670

        203 IF X(4) > 1 THEN 1670

        205 X(1) = (-X(2) ^ -1 * X(4) ^ -1 + 1) / (X(4) ^ -1)

        208 IF -X(1) ^ -2 * X(3) ^ -1 – X(2) * X(3) ^ -1 > -1 THEN 1670

        291 IF X(1) < .1 THEN 1670

        292 IF X(1) > 1 THEN 1670

        293 IF X(2) < 5 THEN 1670

        294 IF X(2) > 10 THEN 1670

        301 IF X(3) < 8 THEN 1670

        302 IF X(3) > 15 THEN 1670

        304 IF X(4) < .01 THEN 1670

        306 IF X(4) > 1 THEN 1670

        463 PD1 = -X(3) ^ .8 * X(4) ^ 1.2

        466 P = PD1

        1111 IF P <= M THEN 1670

        1452 M = P

        1454 FOR KLX = 1 TO 4

            1455 A(KLX) = X(KLX)

        1456 NEXT KLX

    1670 NEXT I

    1889 IF M < -.8 THEN 1999   

    1899 PRINT A(1), A(2), A(3), A(4), M, JJJJ

1999 NEXT JJJJ

This computer program was run with qb64v1000-win [102].  The complete output of one run through -20601.2 is shown below:

.1   10   8.25   .2   -.78415

-31846.4

.1   10   8.31   .2   -.7887091

-30571.7

.1   10   8.23   .2   -.7826288

-30108.52

.1   10   8.06   .2  .7696691

-21525.28

.1   10   8.09   .2   -.7719601

-20601.2

Above there is no rounding by hand; it is just straight copying by hand from the monitor screen. On a personal computer with Processor Intel Pentium CPU G620@ 2.60GHz, 4.00 GB of RAM, 64-bit Operating System, and QB64v1000-win [102], the wall-clock time (not CPU time) for obtaining the output through JJJJ = -20601.2 was 13 minutes, counting from “Starting program…”.  One can compare the computational results above with those in Wang, Zhang, and Gao [99,  p. 1515, Table 1, Example 6].

Acknowledgement

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

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[56] Yubao Liu, Guihe Qin (2014), A hybrid TS-DE algorithm for reliability redundancy optimization problem, Journal of Computers, 9, No. 9, September 2014, pp. 2050-2057.

[57]  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.

[58] Costas D. Maranas, Christodoulos A. Floudas, Global Optimization in Generalized Geometric Programming, pp. 1-42. https://pennstate.pure.elsevier.com/en/publications/global-optimization-in-generalized-geometric-programming

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[60] Mohamed Arezki Mellal, Edward J. Williams (2018). Large-scale reliability-redundancy allocation optimization problem using three soft computing methods. In Mangey Ram, Editor, in Modeling and simulation based analysis in reliability engineering. Published July 2018, CRC Press.

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[67] Max M. J. Opgenoord, Brian S. Cohn, Warren W. Hobburg (August 31, 2017).  Comparison of algorithms for including equality constraints in signomial programming.  ACDL Technical Report TR-2017-1.  August 31 2017.  pp.1-23. 

One can get a Google view of this report.

[68] Rashmi Ranjan Ota, jayanta kumar dASH, A. K. Ojha (2014). A hybrid optimization techniques for solving non-linear multi-objective optimization problem. amo-advanced modelling and optimization, volume 16,number 1, 2014.

[69] R. R. Ota, J. C. Pati, A. K. Ojha (2019). Geometric programming technique to optimize power distribution system. OPSEARCH of the Operational Research Society of India (2019), 56, pp. 282-299.

[70] Panos Y. Papalambros, Douglass J. Wilde, Principles of Optimal Design, Second Edition. Cambridge University Press, 2000.

[71] O. Perez, I. Amaya, R. Correa (2013), Numerical solution of certain exponential and nonlinear diophantine systems of equations by using a discrete particles swarm optimization algorithm. Applied Mathematics and Computation, Volume 225, 1 December, 2013, pp. 737-746.

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Combinning Mathematical Formulation, “What If”, and Discrete Variables To Help Solve Nonlinear Programming Problems: Another Illustration

Combinning Mathematical Formulation, “What If”, and Discrete Variables To Help Solve Nonlinear Programming Problems: Another Illustration

Jsun Yui Wong

Similar to the computer program of the preceding paper, the computer program listed below seeks to solve the following mathematical formulation in Bunday [15, p. 107, Exercises 6, 10], which is as follows:

Minimize

        -X(1) * X(2) * X(3)

subject to

        X(1), X(2), X(3) >=0

        2* X(1) ^ 2+X(2) ^ 2 + 3 * X(3) ^ 2 <= 51.

One notes lines 92, 98 , and 99, which are 92 A(1) = INT(100 * RND * 4) / 100, 98 A(2) = INT(100 * RND * 4) / 100, and 99 A(3) = INT(100 * RND * 4) / 100.    

0 REM   DEFDBL A-Z

1 REM DEFINT I, J, K

2 DIM B(99), N(99), A(200), H(99), L(99), U(99), X(200), D(111), P(111), PS(33), J(99), AA(99), HR(32), HHR(32), LHS(44), PLHS(44), LB(22), UB(22), PX(44), J44(44), PN(22), NN(22)

79 FOR JJJJ = -32000 TO 32000

    89 RANDOMIZE JJJJ

    90 M = -3D+30

    92 A(1) = INT(100 * RND * 4) / 100

    98 A(2) = INT(100 * RND * 4) / 100

    99 A(3) = INT(100 * RND * 4) / 100

    123 FOR I = 1 TO 100000

        129 FOR KKQQ = 1 TO 3

            130 X(KKQQ) = A(KKQQ)

        131 NEXT KKQQ

        139 FOR IPP = 1 TO FIX(1 + RND * 2)

            140 B = 1 + FIX(0 + RND * 3)

            144 IF RND < .5 THEN 160 ELSE GOTO 166

            160 r = (1 – RND * 2) * A(B)

            164 X(B) = A(B) + FIX((RND ^ (RND * 15)) * r)

            165 GOTO 168

            166 IF RND < .5 THEN X(B) = A(B) – FIX(RND * 2) ELSE X(B) = A(B) + FIX(RND * 2)

        168 NEXT IPP

        191 IF X(1) < 0 THEN 1670

        193 IF X(2) < 0 THEN 1670

        195 IF X(3) < 0 THEN 1670

        201 IF (-X(2) ^ 2 – 3 * X(3) ^ 2 + 51) / 2 < 0 THEN 1670

        202 REM           

        204 X(1) = ((-X(2) ^ 2 – 3 * X(3) ^ 2 + 51) / 2) ^ .5

        205 REM          

        291 IF X(1) < 0 THEN 1670

        293 IF X(2) < 0 THEN 1670

        301 IF X(3) < 0 THEN 1670

        463 PD1 = X(1) * X(2) * X(3)

        466 P = PD1

        1111 IF P <= M THEN 1670

        1452 M = P

        1454 FOR KLX = 1 TO 3

            1455 A(KLX) = X(KLX)

        1456 NEXT KLX

    1670 NEXT I

    1889 IF M < 28.612 THEN 1999

    1899 PRINT A(1), A(2), A(3), M, JJJJ

1999 NEXT JJJJ

This computer program was run with qb64v1000-win [102].  The complete output of one run through -31245 is shown below:

2.918253       4.12       2.38       28.61522       -31715

2.900681      4.11      2.4        28.61232      -31338

2.898862      4.13      2.39      28.61379      -31245

Above there is no rounding by hand; it is just straight copying by hand from the monitor screen. On a personal computer with Processor Intel Pentium CPU G620@ 2.60GHz, 4.00 GB of RAM, 64-bit Operating System, and QB64v1000-win [102], the wall-clock time (not CPU time) for obtaining the output through JJJJ = -31245 was 77 seconds, counting from “Starting program…”.  One can compare the computational results above with those in Bunday [15,  p. 126, Exercises 6, 10].

References

Acknowledgement

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

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One can get a Google view of this report.

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[72] Yashpal Singh Raghav, Irfan Ali, Abdul Bari (2014) Multi-Objective Nonlinear Programming Problem Approach in Multivariate Stratified Sample Surveys in the Case of the Non-Response, Journal of Statitiscal Computation ans Simulation 84:1, 22-36, doi:10.1080/00949655.2012.692370.

[73] Rajgopal, Geometric Programming. https://sites.pitt.edu/~jrclass/notes6.pdf

[74] R. V. Rao, P. J. Pawar, J. P. Davim (2010). Parameter optimization of ultrasonic machining pr5cess using nontraditional optimization algorihms. Materials and Manufacturing Processes, 25 (10),1120-1130.

[75] John Rice, Numerical Methods, Software, and Analysis, Second Edition, 1993, Academic Press.

[76] M. J. Rijckaert, X. M. Martens, Comparison of generalized geometric programming algorithms, J. of Optimization, Theory and Applications, 26 (2) 205-242 (1978).

[77] H. S. Ryoo, N. V. Sahinidis (1995), Global Optimization of Nonconvex NLPs and MINLPs with Applications in Process Design. Computers and Chemical Engineering, Vol. 19, No. 5, pp. 551-566, 1995.

[78] Ali Sadollah, Hadi Eskandar, Joong Hoon Kim (2015). Water cycle algorithm for solvinfg constrained multi-objective optimization problems. Applied Soft Computing 27 (2015) 279-298.

[79] Shafiullah, Irfan Ali, Abdul Bari (2015). Fuzzy geometric programming approach in multi-objective multivariate stratified sample surveys in presence of non-respnse, International Journal of Operations Research, Vol. 12, No. 2, pp. 021-035 (2015).

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

[81] Vikas Sharma, Kalpana Dahiya, Vanita Verma (2017). A ranking algorithm for bi-objective quadratic fractional integer programming problems, Optimization, 66:11, 1913-1929.

[82] Donald M. Simmons (1969), One-Dimensional Space Allocation: An Ordering Algorithm. Operations Research, Vol. 17, No. 5 (Sep. – Oct., 1969), pp. 812-826.

[83] G. Stephanopoulos, A. W. Westerberg, The Use of Hestenes’ Method of Multipliers to Resolve

Dual Gaps in Engineering System Optimization. Journal of Optimization Theory and Applications, Vol.15, No. 3, pp. 285-309, 1975.

[84] Hardi Tambunan, Herman Mawengkang (2016). Solving Mixed Integer Non-Linear Programming Using Active Constraint. Global Journal of Pure and Applied Mathematics, Volume 12, Number 6 (2016), pp. 5267-5281. http://www.ripublication.com/gjpam.htm

[85] Mohamed Tawhid, Vimal Savsani (2018). Epsilon-constraint heat transfer search (epsilon-HTS) algorithm for solvinfg multi-objective engineering design problems. journal of computational design and engineering 5 (2018) 104-119.

[86] Frank A. Tillman, Ching-Lai Hwang, Way Kuo (1977). Determining Component Reliability and Redundancy for Optimun System Reliability. IEEE Transactions on Reliability, Vol. R-26, No. 3, Augusr 1977, pp. 162-165.

[87] Jung-Fa Tsai, Han-Lin Li, Nian-Ze Hu (2002).   Global optimization for signomial discrete programming problems in engineering design, Engineering Optimization, 34:6, 613-622.

[88] 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) 10-19. 

[89] Jung-Fa Tsai (2009).   Treatng free variables in generalized geometric programming problems.  Computers and Chemical Enginering 33 (2009) 239-243. 

[90] Jung-Fa Tsai, Ming-Hua Lin (2013).  An improved framewpork for solving NLIPs with signomial terms in the objective or constraints to global optimality, Computers and Chemical Engineering 53 (2013) 44-54. 

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[92] Rahul Varshney, Srikant Gupta, Irfan Ali (2017). An optimum multivariate-multiobjective stratified samplinr design: fuzzy programming approach. Pakistan Journal of Statistics and Operations Research, pp. 829-855, December 2017

[93] Tawan Wasanapradit, Nalinee Mukdasanit, Nachol Chaiyaratana, Thongchai Srinophakun (2011). Solving mixed-integer nonlinear programming problems using improved genetic algorithms. Korean Joutnal of Chemical Engineering 28 (1):32-40 January 2011.

[94] Rahul Varshney, Mradula (2019 May 25). Optimum allocation in multivariate stratified sampling design in the presence of nonresponse with Gamma cost function, Journal of Statistical Computation and Simulation (2019) 89:13, pp. 2454-2467.

[95] Rahul Varshney, Najmussehar, M. J. Ahsan (2012). An optimum multivariate stratified double sampling design in presence of non-response, Optimization Letters (2012) 6: pp. 993-1008.

[96] Rahul Varshney, M. G. M. Khan, Ummatul Fatima, M. J. Ahsan (2015). Integer compromise allocation in multivariate stratified surveys, Annals of Operations Research (2015) 226:659-668.

[97] Rahul Varshney, Srikant Gupta, Irfan Ali (2017). An optimum multivariate-multiobjective stratified samplinr design: fuzzy programming approach. Pakistan Journal of Statistics and Operations Research, pp. 829-855, December 2017

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

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[104] Helen Wu, (2015), Geometric Programming

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Combinning Mathematical Formulation, “What If”, and Discrete Variables To Help Solve Nonlinear Programming Problems: An Illustration

Combinning Mathematical Formulation, “What If”, and Discrete Variables To Help Solve Nonlinear Programming Problems: An Illustration

Jsun Yui Wong

Similar to the computer program of the preceding paper, the computer program listed below seeks to solve the following mathematical formulation in Bunday [15, p. 102 (and p. 92)], which is as follows:

Minimize

  -(X(1)) * (X(2)) * (X(3))

subject to
0<= X(1) <= 20

    0<= X(2) <= 11 

    0<= X(3) <= 42

    X(1) +2 * X(2) + 2 * X(3) <= 72.

One notes lines 181, 182 , and 183, which are 181 X(1) = INT(X(1)), 182 X(2) = INT(X(2)), and 183 X(3) = INT(X(3)).

0 REM DEFDBL A-Z
1 REM DEFINT I, J, K
2 DIM B(99), N(99), A(200), H(99), L(99), U(99), X(200), D(111), P(111), PS(33), J(99), AA(99), HR(32), HHR(32), LHS(44), PLHS(44), LB(22), UB(22), PX(44), J44(44), PN(22), NN(22)
79 FOR JJJJ = -32000 TO 32000

89 RANDOMIZE JJJJ

90 M = -3D+30

92 A(1) = RND * 20

93 A(2) = RND * 11

96 A(3) = RND * 42

123 FOR I = 1 TO 10000

    129 FOR KKQQ = 1 TO 3

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


    139 FOR IPP = 1 TO FIX(1 + RND * 2)

        140 B = 1 + FIX(0 + RND * 3)

        144 IF RND < .5 THEN 160 ELSE GOTO 166

        160 r = (1 - RND * 2) * A(B)

        164 X(B) = A(B) + FIX((RND ^ (RND * 15)) * r)


        165 GOTO 168

        166 IF RND < .5 THEN X(B) = A(B) - FIX(RND * 2) ELSE X(B) = A(B) + FIX(RND * 2)


    168 NEXT IPP

    181 X(1) = INT(X(1))
    182 X(2) = INT(X(2))
    183 X(3) = INT(X(3))
    191 IF X(1) < 0 THEN 1670
    192 IF X(1) > 20 THEN 1670
    193 IF X(2) < 0 THEN 1670
    194 IF X(2) > 11 THEN 1670
    195 IF X(3) < 0 THEN 1670
    200 IF X(3) > 42 THEN 1670

    205 IF X(1) + 2 * X(2) + 2 * X(3) - 72 > 0 THEN 1670
    291 IF X(1) < 0 THEN 1670
    292 IF X(1) > 20 THEN 1670
    293 IF X(2) < 0 THEN 1670
    294 IF X(2) > 11 THEN 1670
    301 IF X(3) < 0 THEN 1670
    399 IF X(3) > 42 THEN 1670

    463 PD1 = (X(1)) * (X(2)) * (X(3))
    466 P = PD1

    1111 IF P <= M THEN 1670
    1452 M = P
    1454 FOR KLX = 1 TO 3

        1455 A(KLX) = X(KLX)
    1456 NEXT KLX
1670 NEXT I
1889 IF M < 2222 THEN 1999
1899 PRINT A(1), A(2), A(3), M, JJJJ

1999 NEXT JJJJ

This computer program was run with qb64v1000-win [102]. Its complete output of one run through JJJJ= -31996 is shown below:

20 11 15 3300 -32000
20 11 15 3300 -31999
20 11 15 3300 -31998
20 11 15 3300 -31997
20 11 15 3300 -31996

Above there is no rounding by hand; it is just straight copying by hand from the monitor screen. On a personal computer with Processor Intel Pentium CPU G620@ 2.60GHz, 4.00 GB of RAM, 64-bit Operating System, and QB64v1000-win [102], the wall-clock time (not CPU time) for obtaining the output through JJJJ = -31996 was 2 seconds, counting from “Starting program…”. One can compare the computational results above with those in Bunday [15, p. 106].

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

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Solving Nonlinear Integer Programming Problems Involving Mixed-Discrete Variables and Free (Negative, Zero, or Positive) Variables: an Illustration

Solving Nonlinear Integer Programming Problems Involving Mixed-Discrete Variables and Free (Negative, Zero, or Positive) Variables: an Illustration

Jsun Yui Wong

Similar to the computer program of the preceding paper, the computer program listed below seeks to solve the following problem:

Minimize

        X(1) ^ 2 * X(2) ^ .816   – X(2) ^ .5 – X(3) ^ 1.2

subject to

         X(1) ^ .8 + X(2) ^ .9 + X(3) ^ .5 >= 16

         X(1) ^ -1.5 + X(2) ^ 1.7 + X(3) ^ 1.2 <= 31

where

        X(1) epsilon {1.1, 3.2, 5.3, 7.4, 9.5, 12.6, 14.7, 16.8 }

        X(2), X(3) epsilon {1.1, 1.2, 1.3, 1.4, 1.5, 2.0, 2.6, 2.7, 2.8, 2.9, 3.1, 3.2, 3.3, 3.4, 3.5, 4.0, 4.6, 4.7, 4.8, 4.9,… 23.1, 23.2, 23.3, 23.4, 23.5, 24.0, 24.6, 24.7, 24.8, 24.9, 25.1, 25.2, 25.3, 25.4, 25.5, 26.0, 26.6, 26.7 }. 

The problem above is based on Program 8 of Li and Lu [51, p. 711, Program 8]:

Minimize

        X(1) ^ 2 * X(2) ^ .816   – X(2) ^ .5 – X(3) ^ 1.2

subject to

         X(1) ^ .8 + X(2) ^ .9 + X(3) ^ .5 >= 16

         X(1) ^ -1.5 + X(2) ^ 1.7 + X(3) ^ 1.2 <= 31

where

        X(1) epsilon {1.1, 3.2, 5.3, 7.4, 9.5, 12.6, 14.7, 16.8}

        X(2), X(3) epsilon {1.1, 1.2, 1.3, 1.4, 1.5, 2.0, 2.6, 2.7, 2.8, 2.9, 3.1, 3.2, 3.3, 3.4, 3.5, 4.0, 4.6, 4.7, 4.8, 4.9,… 23.1, 23.2, 23.3, 23.4, 23.5, 24.0, 24.6, 24.7, 24.8, 24.9, 25.1, 25.2, 25.3, 25.4, 25.5, 26.0, 26.6, 26.7 }. 

One notes that because of …1.5, 2.0, 2.6,…, etc., this latter X(3) contains less possible (numerical) values than the former X(3), for example.

The plan is to use the former to help solve problems like the latter, with its …1.5, 2.0, 2.6,…, etc.

0 DEFDBL A-Z

1 REM DEFINT I, J, K

2 DIM B(99), N(99), A(200), H(99), L(99), U(99), X(200), D(111), P(111), PS(33), J(99), AA(99), HR(32), HHR(32), LHS(44), PLHS(44), LB(22), UB(22), PX(44), J44(44), PN(22), NN(22)

79 FOR JJJJ = -32000 TO 32000

    89 RANDOMIZE JJJJ

    90 M = -3D+30

    91 IF RND < 1 / 8 THEN A(1) = 1.1 ELSE IF RND < 1 / 7 THEN A(1) = 3.2 ELSE IF RND < 1 / 6 THEN A(1) = 5.3 ELSE IF RND < 1 / 5 THEN A(1) = 7.4 ELSE IF RND < 1 / 4 THEN A(1) = 9.5 ELSE IF RND < 1 / 3 THEN A(1) = 12.6 ELSE IF RND < 1 / 2 THEN A(1) = 14.7 ELSE A(1) = 16.8

    93 A(2) = 1 + (FIX(RND * 27)) * .1

    94 A(3) = 1 + (FIX(RND * 27)) * .1

    123 FOR I = 1 TO 50000

        129 FOR KKQQ = 1 TO 3

            130 X(KKQQ) = A(KKQQ)

        131 NEXT KKQQ

        133 FOR IPP = 1 TO FIX(1 + RND * 2)

            135 IF RND < 1 / 8 THEN X(1) = 1.1 ELSE IF RND < 1 / 7 THEN X(1) = 3.2 ELSE IF RND < 1 / 6 THEN X(1) = 5.3 ELSE IF RND < 1 / 5 THEN X(1) = 7.4 ELSE IF RND < 1 / 4 THEN X(1) = 9.5 ELSE IF RND < 1 / 3 THEN X(1) = 12.6 ELSE IF RND < 1 / 2 THEN X(1) = 14.7 ELSE X(1) = 16.8

            139 REM   FOR IPP = 1 TO FIX(1 + RND * 2)

            140 B = 2 + FIX(RND * 2)

            144 IF RND < .5 THEN 160 ELSE GOTO 167

            160 r = (1 – RND * 2) * A(B)

            164 X(B) = A(B) + FIX((RND ^ (RND * 15)) * r)

            165 GOTO 168

            166 REM F RND < .5 THEN X(B) = A(B) – FIX(RND * 4) ELSE X(B) = A(B) + FIX(RND * 4)

            167 X(B) = 1 + (FIX(RND * 27)) * .1

        168 NEXT IPP

        202 IF X(1) ^ .8 + X(2) ^ .9 + X(3) ^ .5 < 16 THEN 1670

        204 IF X(1) ^ -1.5 + X(2) ^ 1.7 + X(3) ^ 1.2 > 31 THEN 1670

        291 IF X(1) < 1.1 THEN 1670

        292 IF X(1) > 16.8 THEN 1670

        293 IF X(2) < 1.1 THEN 1670

        294 IF X(2) > 26.7 THEN 1670

        301 IF X(3) < 1.1 THEN 1670

        302 IF X(3) > 26.7 THEN 1670

        463 PD1 = -X(1) ^ 2 * X(2) ^ .816 + X(2) ^ .5 + X(3) ^ 1.2

        466 P = PD1

        1111 IF P <= M THEN 1670

        1452 M = P

        1454 FOR KLX = 1 TO 3

            1455 A(KLX) = X(KLX)

        1456 NEXT KLX

    1670 NEXT I

    1889 IF M < -685.11111 THEN 1999

    1899 PRINT A(1), A(2), A(3), M, JJJJ

1999 NEXT JJJJ

This computer program was run with qb64v1000-win [102].  Its complete output of one run through JJJJ= -29575 is shown below:

16.8      3.1      14         -685.0154632676962

-31866

16.8      3      14.3         -665.6738562024938

-29997

16.8      3.1      14         -685.0154632676962

-29575

Above there is no rounding by hand; it is just straight copying by hand from the monitor screen. On a personal computer with Processor Intel Pentium CPU G620@ 2.60GHz, 4.00 GB of RAM, 64-bit Operating System, and QB64v1000-win [102], the wall-clock time (not CPU time) for obtaining the output through JJJJ = -29575 was 140 seconds, counting from “Starting program…”.  One can compare the computational results above with those in Li and Lu [51,  p. 712]. 

(16.8     3     14.3) shown above at JJJJ= -29997 is not a feasible solution to the Li and Lu problem [51, p. 711, Program 8].

Acknowledgement

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

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[91] Jung-Fa Tsai, Ming-Hua Lin, Duan-Yi Wen (16 September 2020).  Global optimization for mixed-discrete structural design.  Symmetry 2020, 12, 1529

One can get a Google view of this article.  www.mdpi.com/journal/symmetry.

[92] Rahul Varshney, Srikant Gupta, Irfan Ali (2017). An optimum multivariate-multiobjective stratified samplinr design: fuzzy programming approach. Pakistan Journal of Statistics and Operations Research, pp. 829-855, December 2017

[93] Tawan Wasanapradit, Nalinee Mukdasanit, Nachol Chaiyaratana, Thongchai Srinophakun (2011). Solving mixed-integer nonlinear programming problems using improved genetic algorithms. Korean Joutnal of Chemical Engineering 28 (1):32-40 January 2011.

[94] Rahul Varshney, Mradula (2019 May 25). Optimum allocation in multivariate stratified sampling design in the presence of nonresponse with Gamma cost function, Journal of Statistical Computation and Simulation (2019) 89:13, pp. 2454-2467.

[95] Rahul Varshney, Najmussehar, M. J. Ahsan (2012). An optimum multivariate stratified double sampling design in presence of non-response, Optimization Letters (2012) 6: pp. 993-1008.

[96] Rahul Varshney, M. G. M. Khan, Ummatul Fatima, M. J. Ahsan (2015). Integer compromise allocation in multivariate stratified surveys, Annals of Operations Research (2015) 226:659-668.

[97] Rahul Varshney, Srikant Gupta, Irfan Ali (2017). An optimum multivariate-multiobjective stratified samplinr design: fuzzy programming approach. Pakistan Journal of Statistics and Operations Research, pp. 829-855, December 2017

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Direct Finding Multiple Optimal Solutions in One Run of a Generalized Geometric Programming Problem: an Illustration

Direct Finding Multiple Optimal Solutions in One Run of a Generalized Geometric Programming Problem: an Illustration

Jsun Yui Wong

Similar to the computer program of the preceding paper, the computer program listed below aims to solve directly the following problem from Liu, Wang, and Liu [56, p. 12, Example 4.4]:

Minimize

 .3578 * X(3) ^ .1 + .8357 * X(1) * X(5)

subject to

        .00002584 * X(3) * X(5) – .00006663 * X(2) * X(5) – .0000734 * X(1) * X(4) <= 5

        .00085305 * X(2) * X(5) + .00009395 * X(1) * X(4) – .00033085 * X(3) * X(5) <= 5

        1.3294 * X(2) ^ -1 * X(5) ^ -1 – .4200 * X(2) * X(5) ^ -1 – .30575 * X(2) ^ -1 * X(3) ^ -2 * X(5) ^ -1 <= 5

        .00024186 * X(2) * X(5) + .00010159 * X(1) * X(2) + .00007379 * X(3) ^ 2 <= 5

        2.1327 * X(3) ^ -1 * X(5) ^ -1 – .26680 * X(1) * X(5) ^ -1 – .40584 * X(4) * X(5) ^ -1 <= 5

       .000229955 * X(3) * X(5) – .00007992 * X(1) * X(3) + .00012157 * X(3) * X(4) <= 5

       1<=  X(i) <= 60, i=1, 2, 3,…, 6.

0 DEFDBL A-Z

1 REM DEFINT I, J, K

2 DIM B(99), N(99), A(2002), H(99), L(99), U(99), X(2002), D(111), P(111), PS(33), J(99), AA(99), HR(32), HHR(32), LHS(44), PLHS(44), LB(22), UB(22), PX(44), J44(44), PN(22), NN(22)

79 FOR JJJJ = -32000 TO 32000

    89 RANDOMIZE JJJJ

    90 M = -3D+30

    103 FOR j44 = 1 TO 5

        107 A(j44) = 1 + RND * 59

    109 NEXT j44

    123 FOR I = 1 TO 50000

        129 FOR KKQQ = 1 TO 5

            130 X(KKQQ) = A(KKQQ)

        131 NEXT KKQQ

        139 FOR IPP = 1 TO FIX(1 + RND * 4)

            140 B = 1 + FIX(RND * 5)

            144 IF RND < .5 THEN 160 ELSE GOTO 167

            160 r = (1 – RND * 2) * A(B)

            164 X(B) = A(B) + (RND ^ (RND * 15)) * r

            165 GOTO 168

            167 IF RND < .5 THEN X(B) = A(B) – FIX(RND * 4) ELSE X(B) = A(B) + FIX(RND * 4)

        168 NEXT IPP

        172 FOR j44 = 1 TO 5

            173 IF X(j44) < 1 THEN 1670

            175 IF X(j44) > 60 THEN 1670

        176 NEXT j44

        302 IF .00002584 * X(3) * X(5) – .00006663 * X(2) * X(5) – .0000734 * X(1) * X(4) > 5 THEN 1670

        303 IF .00085305 * X(2) * X(5) + .00009395 * X(1) * X(4) – .00033085 * X(3) * X(5) > 5 THEN 1670

        304 IF 1.3294 * X(2) ^ -1 * X(5) ^ -1 – .4200 * X(2) * X(5) ^ -1 – .30575 * X(2) ^ -1 * X(3) ^ -2 * X(5) ^ -1 > 5 THEN 1670

        305 IF .00024186 * X(2) * X(5) + .00010159 * X(1) * X(2) + .00007379 * X(3) ^ 2 > 5 THEN 1670

        306 IF 2.1327 * X(3) ^ -1 * X(5) ^ -1 – .26680 * X(1) * X(5) ^ -1 – .40584 * X(4) * X(5) ^ -1 > 5 THEN 1670

        307 IF .000229955 * X(3) * X(5) – .00007992 * X(1) * X(3) + .00012157 * X(3) * X(4) > 5 THEN 1670

        461 PD1 = -.3578 * X(3) ^ .1 – .8357 * X(1) * X(5)

        466 P = PD1

        1111 IF P <= M THEN 1670

        1452 M = P

        1454 FOR KLX = 1 TO 5

            1455 A(KLX) = X(KLX)

        1456 NEXT KLX

    1670 NEXT I

    1889 IF M < -999999999999 THEN 1999

    1899 PRINT A(1), A(2), A(3), A(4), A(5), M, JJJJ

1999 NEXT JJJJ

This computer program was run with qb64v1000-win [101].  Its complete output of one run through JJJJ= -31999 is shown below:

 1      3.489730346287245         1.000000000000006  

 9.661688138816091      1         -1.1935      -32000

 1.00000000000002        3.816821831995267     1.00000000000002

 5.502263832853543      1.000000000000022    -1.193500000000035

-31999

Above there is no rounding by hand; it is just straight copying by hand from the monitor screen. On a personal computer with Processor Intel Pentium CPU G620@ 2.60GHz, 4.00 GB of RAM, 64-bit Operating System, and QB64v1000-win [101], the wall-clock time (not CPU time) for obtaining the output through JJJJ = -31999 was 2 seconds, counting from “Starting program…”.  One can compare the computational results above with those in Liu, Wang, and Liu [56,  p. 12, Example 4.4].

Acknowledgement

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

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