Example error message
The 'OptLowerBound' attribute of Decision 'Theta' should contain a single value since Decision 'Theta' is a scalar decision variable (its OptDimensions attribute does not list any indexes). Currently its 'OptLowerBound' attribute is specified as an unindexed list.
The OptDimensions attribute specifies the indexes of a decision variable that are part of an optimization problem. When this attribute is not set, then the decision variable is taken to be scalar, such that the optimization will search for a single numeric value to solve the optimization problem.
If you see this message, your decision variable is either missing the OptDimensions attribute, or has it set to an empty list, in either case, specifying that your decision is scalar. However, the indicated attribute (OptLowerBound in the example message) has multiple values in the form of an unindexed list. Since the decision variable is scalar, it is expected that only a single lower bound would be specified.
Most likely, the desired fix will be to replaced the list in OptLowerBound attribute (or whichever attribute is listed in your error message) with a single value.
Or, you may have forgotten to specify the index of your decision variable in the OptDimensions attribute. In that case, list the index, or indexes, in OptDimensions.
In less common cases, your intention may be to array-abstract over different possible lower bounds (or different possible values for whichever attribute is listed in the message that you see). That is still possible as long as the value in the attribute is indexed by a real index, and not just an unindexed list. In this case, you can replace your list with a general expression that computes an array. If you do this, it is preferable (for several stylistic reasons) to place the expression or table for the lower bound in a separate variable object, and then just place the identifier of that variable in the attribute for the decision variable.