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This study, that will be presented as two parts, develops a computational approach to a class of continuous-time generalized fractional programming problems. The parametric method for finite-dimensional generalized fractional programming is extended to problems posed in function spaces. The developed method is a hybrid of the parametric method and discretization approach. In this paper (Part I), some properties of continuous-time optimization problems in parametric form pertaining to continuous-time generalized fractional programming problems are derived. These properties make it possible to develop a computational procedure for continuous-time generalized fractional programming problems. However, it is notoriously difficult to find the exact solutions of continuous-time optimization problems. In the accompanying paper (Part II), a further computational procedure with approximation will be proposed. This procedure will yield bounds on errors introduced by the numerical approximation. In addition, both the size of discretization and the precision of an approximation approach depend on predefined parameters. [ABSTRACT FROM AUTHOR]

The theory presented in Part I (Wen in J. Optim. Theory Appl. 2012) of this study led to a theoretical parametric procedure for continuous-time generalized fractional programming problems. In this paper (Part II), an interval-type computational procedure by combining the parametric method and discretization approach is proposed. The proposed method is promising particularly when it is acceptable to find an effective, but near-optimal value in an efficient manner. Once the error tolerance is predetermined, we can determine the size of discretization in advance such that the accuracy of the corresponding approximate solution can be controlled within the predefined error tolerance. Hence, the trade-off between the quality of the results and the simplification of the problem can be controlled by the decision maker. Finally, we provide some numerical examples to implement our proposed method. [ABSTRACT FROM AUTHOR]