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This paper presents a simplex-based solution procedure for the multiple objective linear fractional programming problem. By (1) departing slightly from the traditional notion of efficiency and (2) augmenting the feasible region as in goal programming, the solution procedure solves for all weakly efficient vertices of the augmented feasible region. The article discusses the difficulties that must be addressed in multiple objective linear fractional programming and motivates the solution algorithm that is developed. [ABSTRACT FROM AUTHOR]

In this paper we combine the Tchebycheff method of Steuer and Choo with Wierzbicki's Aspiration Criterion Vector method in order to form an improved procedure for interactive multiple objective programming. The Combined procedure is sensible because the Tchebycheff and Aspiration Criterion Vector methods possess complementary distinguishing characteristics, solve similar optimization problems to probe the nondominated set, and share a similar computer/user interface. In the early iterations, Tchebycheff probes of the nondominated set might be conducted to locate promising neighborhoods of search. In later iterations, Aspiration Criterion Vector probes might be used to pinpoint a final solution. Computational experience is reported showing the improved effectiveness of the Combined Procedure when employed in this fashion when compared against the Tchebycheff and Aspiration Criterion Vector methods run separately. [ABSTRACT FROM AUTHOR]