next up previous
Next: 3.2 Indicator and Data Up: 3.1 Introduction to the Previous: 3.1.3 Numerical Values

3.1.4 An Example

Before we give the complete syntax for an SDIF file, we give an illustrative example. In order to exhibit as many constructs as possible, we consider how we might encode the example in Section 2.5. We urge the reader to study this section in detail. As always, there are many possible ways of specifying a particular problem; we give one in Figures 3.1 and 3.2, pages [*] and [*]. The horizontal and vertical lines are merely included to indicate the extent of data fields. The actual widths of the fields are given at the top of the figure, and the column numbers given at its foot.

The SDIF file naturally divides into two parts. In the first part, lines 2 to 39 of the figure, we specify information regarding linear functions used in the example. In the second part, lines 40 to 93, we specify nonlinear information. The first part is merely an extension of the MPS input format; the second part is new.

The file must always start with a NAME card, on which a name (in this case EG3) for the example may be given (line 1), and must end with an ENDATA card (line 93). A comment is inserted at the end of line 1 as to the source of the example. The character $ identifies the remainder of the line as a comment; the comment is ignored when interpreting the input file.

We next specify names of parameters which will occur frequently in specifying the example (lines 2 to 5). In our case the integer and real parameters 1 and ONE are given along with N, a problem dimension -- here N is set to 100, but it would be trivial to change the example in 6 to allow variables $ x_1
,\ldots, x_n$ for any $n$. We make a comment to this effect on line 4; any card with the character * in column 1 is a comment card and its content is ignored when interpreting the input file.

We now name the problem variables and groups (in our example objective function and constraints) used. The groups may be specified before or after the variables. We choose here to name the groups first. The objective function will be known as OBJ (line 7); the character N in field 1 specifies that this is an objective function group. The inequality constraints (2.19) and (2.20) are named ${\tt CONLE1},\ldots, {\tt CONLE99}$ and ${\tt CONGE1},\ldots, {\tt CONGE100}$ respectively. Rather than specify them individually, a do-loop is used to make an array definition. Thus the constraints ${\tt CONLE1,\ldots, CONLE99}$ are defined en masse on lines 9 to 11 with the do-loop index I running from the previously defined value $1$ to the value NM1. The integer parameter, NM1, is defined on line 8 to be the sum of N and the value ${\tt -1}$ and in our case will be 99. The characters XL in field 1 of line 10 indicate that an array definition is being made (the ${\tt X}$) and that the groups are less-than-or-equal-to constraints (the L). The do-loop introduced on line 9 with the characters DO in field 1 is terminated on line 11 with the characters ND in its first field. In a similar way, the constraints ${\tt CONGE1,\ldots, CONGE99}$ are defined all together on lines 12 to 14; that these constraints involve bounds on both sides is taken care of by considering them to be greater-than-or-equal-to constraints (XG) on line 13 and later specifying the additional upper bounds in the RANGES section (lines 26 to 29). Finally, the equality constraint (2.21) is to be called CONEQ (line 15); the character E in field 1 specifies that this is an equality constraint group.

Having named the groups, we next name the problem variables. At the same time, we include the coefficients of all the linear elements used. The variables are named ${\tt X1},\ldots, {\tt X100}$ and Y; an array declaration is made for the former set on lines 17 to 19 and Y is defined on line 20. The character X in field 1 of line 18 indicates that an array definition is used. Only the objective function (2.18), inequality constraint (2.19) and equality constraint groups (2.21) contain linear elements. As well as introducing Y, line 20 also specifies that the linear element associated with group OBJ (field 3) involves variable Y, and that Y 's coefficient in the linear element is 1.0 (field 4). A do-loop is now used in lines 21 to 23 to show that the linear elements for constraints (2.19) also use the variable Y. It is assumed that unless a variable is explicitly identified with a linear element, the element is independent of that variable. Thus, although (2.21) uses a linear element, the element is constant and need not be specified in the VARIABLES section.

The only remaining part of the linear elements which must be specified is the constant term. Again, only nonzero constants need be given. For our example, only the equality constraint group (2.21) has a nonzero constant term and this data is specified on lines 24 and 25. The string C1 in field 2 of line 25 is the name given to a specific set of constants. In general, more than one set of constants may be specified in the SDIF file and the relevant one selected in a postprocessing stage. Here, of course, we only have one set.

As we have seen, the inequality constraint groups (2.20) are bounded from above as well as from below. In the RANGES section (lines 26 to 30) we specify these upper bounds (or range constraints as they are sometimes known). The numerical values ${\scriptstyle \frac{1}{2}}$ are specified for each bound for the relevant groups in an array definition on line 28; the string R1 in field 2 is once again a name given to a specific set of range values as it is possible to define more than one set in the RANGES section.

We now turn to the simple bounds (2.22) which are specified in lines 30 to 36 of the example. All problem variables are assumed to have lower bounds of zero and no upper bounds unless otherwise specified. All but one of the variables for our example have lower bounds of $-1$. We thus change the default value for the value of the lower bound on line 31 - the set of bounds is named BND1. The character L specifies that it is the lower bound default that is to be changed. The string 'DEFAULT' in field 3 indicates that the default is being changed. The variable $x_i$ is given an upper bound of $i$. We encode that in a do-loop on lines 32 to 35 of the figure. The do-loop index I is an integer. We change its current value to a real on line 33 and assign that value as the upper bound on line 34. The character Z in field 1 of this line indicates that an array definition is being made and that the data is taken from a parameter in field 5 (as opposed to a specified numerical value in field 4) and the character U specifies that the upper bound value is to be assigned. The variable y is unbounded or, as it is often known, free. This is specified on line 36, the string FR in field 1 indicating that Y is free.

The final ``linear'' piece of information given is an estimate of the solution to the problem (if known) or at least a set of values from which to start a minimization algorithm. This information is given on lines 37 to 39. For our problem, we choose the values $x_i =
{\scriptstyle \frac{1}{2}}, 1 \leq i \leq 100$ and $y = 0$. Unless otherwise specified, all starting values take a default of zero. We change that default on line 38 to ${\scriptstyle \frac{1}{2}}$ -- the set of starting values are named START1 -- and then specify the individual value for the variable Y on line 39.

We now specify the nonlinear information. Firstly, we recall that there is a quadratic objective group, $x_1^2 + 2 x_1^{ } x_{100}^{ } \equiv {\scriptstyle \frac{1}{2}}( 4 x_1 x_1 +
2 x_1 x_{100} + 2 x_{100} x_1 )$. We need to specify the nonzero coefficients of the terms $x_j x_k$, and in our cases these are $h_{1,1} = 4$ and $h_{1,100} = h_{100,1} = 2$. The rule that we adopt is that there is no need to supply both nonzeros $h_{j,k}$ and $h_{k,j}$ since they are the same, and that one (whichever is unimportant) suffices. Thus $h_{1,1} = 4$ and we (arbitrarily) choose to give $h_{1,100} = 2$. In the QUADRATIC section on lines 39a to 39b, we indicate that the quadratic objective has two terms involving ${x_1}$; the coefficient 4 is given for the ${x_1^2 \equiv x_1^{ } x_1^{ }}$ term, while that for the ${x_1 x_{100}}$ term is assigned the value 2.

Next, we saw in Section 2.5 that there are four element types for the problem, being of the form (i) $(v_1 - v_2 ) v_3$, (ii) $p_1 v_1 v_2$, (iii) $\sin v_1$ and (iv) $(v_1 + v_2 )^2$. In the ELEMENT TYPE section on lines 40 to 48, we record details of these types. We name the four types (i)-(iv) 3PROD, 2PROD, SINE and SQUARE respectively. For 3PROD, we define the elemental variables (lines 41 and 42) to be V1, V2 and V3 and the internal variables (line 43) to be U1 and U2. Elemental variables may be defined, two to a line, on lines for which field 1 is EV. Internal variables, on the other hand, are defined on lines with IV in field 1. Similar definitions are made for 2PROD (line 44), SINE (line 46) and SQUARE (line 47). The type 2PROD also makes use of a parameter $p_1$. This is named P1 on line 45 for which field 1 reads EP.

Having specified the element types, we next specify individual nonlinear elements in the ELEMENT USES section. As we have seen, the objective function group uses a single nonlinear element of type 3PROD. We name this particular element OBJ1. On line 50, the character T in field 1 indicates that the OBJ1 is of type 3PROD. The assignment of problem to elemental variables is made on lines 51 to 53. Problem variables X1 and X2 are assigned to elemental variables V1 and V3; the assignment is indicated by the character V in field 1. In order to assign $x_{100}$ (or in general $x_n$) to $v_2$, we assign the array entry X(N) to V2. Notice that as an array element is being used, this must be specially flagged (ZV in field 1) as otherwise the wrong variable (called X(N) rather than X100, which is the expanded form of X(N)) would be assigned. There are two nonlinear elements for each inequality constraint group (2.19), each being of the same type 2PROD. We name these elements ${\tt CLEA1,\ldots, CLEA99}$ and ${\tt CLEB1,\ldots,
CLEB99}$. The assignments are made on lines 54 to 67 within a do-loop. On lines 56 and 60 the elements are named and their types assigned.

As array assignments are being used, field 1 for both lines contains the string XT. The elemental variables are then associated with problem variables on lines 57-58 and 61-62 respectively. Again array assignments are used and field 1 contains the string ZV. Notice that on line 58 $v_2$ is assigned the problem variable $x_{i+1}$, where the index IP1 is defined as the sum of the index I and the integer value 1 on line 55. It remains to assign values for the parameter $p_1$ for each element. This is straightforward for the elements ${\tt CLEA1,\ldots, CLEA99}$ as the required value is always 1 and the assignment is made on line 59 on a card with first field XP. The remaining elements have varying parameter values ${1 + 2/i}$. This value is calculated on lines 63 to 65 and assigned on line 66. Line 63 assigns REALI to have the floating point value of the index I. This new value is then divided into the value 2 on line 64 and the value assigned to ONE is added to the resulting value on the final line. Thus the parameter 2OVAI+1 holds the required value of $p_1$ and the array assignment is made on line 66. On this line the string ZP indicates that an array assignment is being made, taking its value from the parameter 2OVAI+1 in field 4 (the Z) and that the elemental parameter P1 in field 3 is to be assigned (the P). The definition of the nonlinear elements for the remaining constraint groups is straightforward. The inequality constraints (2.20) each use a single element, named ${\tt CGE1,\ldots, CGE100}$, of type SINE and the appropriate array assignments are made on lines 68 to 70. Finally, the equality constraint (2.21) is named CEQ1 and typed SQUARE with appropriate elemental variable assignments on lines 72 to 74.

We next need to specify the nontrivial group types. This is done in the GROUP TYPE section on lines 75 to 77. We saw in Section 2.5 that a single nontrivial group, $p_1
\alpha^2$, is required. On line 76, the name PSQUARE is given for the type and the group type variable ${\tt\alpha}$ is named ${\tt ALPHA.}$ The string GV pin field 1 indicates that a type and its variable are to be defined. On the following line field 1 is GP and this is used to announce that the group type parameter $p_1$ is named P1.

Finally, we need to allocate nonlinear elements to groups and specify what type the resulting groups are to be. This takes place within the GROUP USES section which runs from line 78 to 90. The objective function group is nontrivial and its type is announced on line 79. The group uses the single nonlinear element OBJ1 specified on line 80 and the group-type parameter $p_1$ is set to the value ${\scriptstyle \frac{1}{2}}$ on the next line. The characters T, E and P in the first fields of these three cards announce their purposes. The inequality groups (2.19) each use two nonlinear elements, but the groups themselves are trivial (and thus their types do not have to be made explicit). The assignment of the elements to each group is made in an array definition on lines 82 to 84; line 83 is flagged as assigning elements to a group with the string XE in field 1. The second set of inequality constraints (2.20) use the nontrivial group type PSQUARE with parameter value 1. Each group uses a single nonlinear element and the appropriate array assignments are contained on lines 85 to 89. Lastly the trivial equality constraint group (2.21) is assigned the nonlinear element CEQ1 on line 90.

The definition of the problem is now complete. However, it often helps the intended minimization program if known lower and upper bounds on the possible values of the objective function can be given. For our example, the objective function (2.18) cannot be smaller than zero. This data is specified on lines 91 and 92. The string LO in field 1 of line 92 indicates that a lower bound is known for the value of (2.18). The string OBOUND in field 2 of this line is a name given to this known bound. The value of the lower bound now follows in field 4. No upper bound need be specified as the function is initially assumed to lie between plus and minus infinity.

Figure 3.1: SDIF file (part 1) for the example of Section 2.5
% latex2html id marker 9575
...iptsize 50}~~~~~~~~~{\scriptsize 61}}\\
\end{tabular} \end{center} \end{figure}

Figure 3.2: SDIF file (part 2) for the example of Section 2.5
...iptsize 50}~~~~~~~~~{\scriptsize 61}}\\
\end{tabular} \end{center} \end{figure}

next up previous
Next: 3.2 Indicator and Data Up: 3.1 Introduction to the Previous: 3.1.3 Numerical Values