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In this paper, a model of a linear multilevel programming problem with dominated objective functions (LMPPD(l)) is proposed, where multiple reactions of the lower levels do not lead to any uncertainty in the upper-level decision making. Under the assumption that the constrained set is nonempty and bounded, a necessary optimality condition is obtained. Two types of geometric properties of the solution sets are studied. It is demonstrated that the feasible set of LMPPD(l) is neither necessarily composed of faces of the constrained set nor necessarily connected. These properties are different from the existing theoretical results for linear multilevel programming problems. [ABSTRACT FROM AUTHOR]

Let X be a partially ordered real Banach space, let a, b∈ X with a≤ b. Let φ be a bounded linear functional on X. We say that X satisfies the box-optimization property (or X is a BOP space) if the box-constrained linear program: max 〈 φ, x〉, s.t. a≤ x≤ b, has an optimal solution for any φ, a and b. Such problems arise naturally in solving a class of problems known as interval linear programs. BOP spaces were introduced (in a different language) and systematically studied in the first author’s doctoral thesis. In this paper, we identify new classes of Banach spaces that are BOP spaces. We present also sufficient conditions under which answers are in the affirmative for the following questions: [ABSTRACT FROM AUTHOR]

In this paper, we discuss here-and-now type stochastic programs with equilibrium constraints. We give a general formulation of such problems and study their basic properties such as measurability and continuity of the corresponding integrand functions. We discuss also the consistency and rate of convergence of sample average approximations of such stochastic problems. [ABSTRACT FROM AUTHOR]

In this paper, a linear bilevel programming problem (LBP) is considered. Local optimality in LBP is studied via two related problems (P) and P(M). Problem (P) is a one-level model obtained by replacing the innermost problem of LBP by its KKT conditions. Problem P(M) is a penalization of the complementarity constraints of (P) with a penalty parameter M, Characterizations of a (strict) local solution of LBP are derived, in particular, the concept of equilibrium point of P(M) is used to characterize the local optima of (P) and LBP. [ABSTRACT FROM AUTHOR]

This paper presents a modified version of the L-shaped method (Refs. 1–5), used to solve two-stage stochastic linear programs with fixed recourse, by employing the implicit LX method and the implicit LP method (Refs. 6–9) of the ABS class of methods. By exploiting the properties and special structure of the ABS class and applying these to the simplex method, the number of arithmetic operations is greatly decreased. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the properties of the optimal solutions obtained when we translate the concepts of perfect, proper, and weakly proper solutions from the context of linear complementarity to the framework of linear programming. [ABSTRACT FROM AUTHOR]

With reference to a multiobjective two-person nonzero-sum game, we define nondominated equilibrium solutions and provide a necessary and sufficient condition for a pair of mixed strategies to be a nondominated equilibrium solution. Using the necessary and sufficient condition, we formulate a mathematical programming problem yielding nondominated equilibrium solutions. We give a numerical example and demonstrate that nondominated equilibrium solutions can be obtained by solving the formulated mathematical programming problem. [ABSTRACT FROM AUTHOR]