Vector processing approach to constrained network problems

Modification of algorithms designed for scalar computing, to take advantage of vector processing, raises several challenges. This article presents the vectorization of the primal simplex based network algorithm and results in a 50% improvement in computational time. One of the major contributors to this improvement is the matching of the size of the pricing candidate list to the vector register size. The side constraints are relaxed into a single surrogate constraint. The single constraint network algorithm is vectorized and used as the basis for solving large-scale constrained network problems. Computational experiments are presented which illustrate the vectorization of the network code as well as the ability of the surrogate constraint approach to deal with large constrained network problems.     

An infiltration game on k arcs

An infiltrator, starting at a safe base, tries to pass, undetected by a guard and within a time limit, along one of k nonintersecting arcs to a safe destination. Optimal strategies and the value are obtained for this discrete zero-sum search-evasion game.     

Two‐dimensional failure modeling with minimal repair

In this paper, we discuss two‐dimensional failure modeling for a system where degradation is due to age and usage. We extend the concept of minimal repair for the one‐dimensional case to the two‐dimensional case and characterize the failures over a two‐dimensional region under minimal repair. An application of this important result to a manufacturer's servicing costs for a two‐dimensional warranty policy is given and we compare the minimal repair strategy with the strategy of replacement of failure. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004.     

Concave envelopes of monomial functions over rectangles

The construction of convex and concave envelopes of real‐valued functions has been of interest in mathematical programming for over 3 decades. Much of this interest stems from the fact that convex and concave envelopes can play important roles in algorithms for solving various discrete and continuous global optimization problems. In this article, we use a simplicial subdivision tool to present and validate the formula for the concave envelope of a monomial function over a rectangle. Potential algorithmic applications of this formula are briefly indicated. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

Optimizability of utility and value functions

For more than a decade, multiattribute utility/value theory and multiobjective mathematical programming have offered different approaches to similar problems. Unfortunately, the two areas have developed with little interaction in spite of their common aims. We consider the use of utility/value functions in a mathematical programming framework, and demonstrate that these functions often possess desirable properties from an optimization point of view. We conclude that a hybridization of approaches is more viable than is perhaps commonly assumed.     

A note on the optimality conditions for the bilevel programming problem

A counterexample is given to demonstrate that previously proposed necessary conditions for the bilevel programming problem are not correct. An interpretation of the difficulty is given by appealing to a “theorem of alternative” result presented in the original work.     

A one-dimensional infiltration game

Minimax strategies are obtained for an infiltration game in which one player must move through a one-dimensional interval defended by the other player.