An easy solution for a special class of fixed charge problems

The fixed charge problem is a mixed integer mathematical programming problem which has proved difficult to solve in the past. In this paper we look at a special case of that problem and show that this case can be solved by formulating it as a set-covering problem. We then use a branch-and-bound integer programming code to solve test fixed charge problems using the setcovering formulation. Even without a special purpose set-covering algorithm, the results from this solution procedure are dramatically better than those obtained using other solution procedures.     

KICKING THE HORNETS’ NEST

This article applies the concept of nuclear ambivalence to the case of the Islamic Republic of Iran. Nuclear ambivalence differs from other approaches to understanding nuclear proliferation in that it focuses on the deeply misunderstood relationship between the two potential uses of nuclear power: energy and weapons. According to this theory, the civilian applications of nuclear technology cannot be separated from the potential military applications and vice versa. Ambivalence, therefore, extends into the realm of states’ nuclear intentions, making it impossible to know with certainty what a potential proliferator's “true” intentions are. This article will demonstrate that the concept of nuclear ambivalence applies in the case of Iran, suggesting that current international nonproliferation efforts run the risk of encouraging rather than discouraging Iranian weaponization. The final section outlines recommendations for policy makers to reverse this counterproductive nonproliferation approach.     

Democracy and peace: Reply to oneal and russett

The criticism of James, Solberg and Wolfson (JSW) (1999) by Oneal and Russett (OR) is not responsive to the methodologica] issues at stake. JSW argued that war is an endogenous feature of the world political and economic system. If its causes are to be measured, it must be as a structural equation in a simultaneous system. Wedded to the idea that “democracies never fight each other,” OR rely on a single equation to justify their view. JSW claim that such an equation may be an ad hoc reduced form with no causal implications unless the equation is explicitly identified as a structural equation. JSW expand the model to explain democracy and conflict as two endogenous variables. JSW do not claim to have discovered the true relationships between these variables by their minimal expansion of the structural relation. They do show that unless these (and other) variables are treated as part of a system, the results are unstable, contradictory, of minimal size and not a reliable guide to public policy.     

Determining adjacent vertices on assignment polytopes

To rank the solutions to the assignment problem using an extreme point method, it is necessary to be able to find all extreme points which are adjacent to a given extreme solution. Recent work has shown a procedure for determining adjacent vertices on transportation polytopes using a modification of the Chernikova Algorithm. We present here a procedure for assignment polytopes which is a simplification of the more general procedure for transportation polytopes and which also allows for implicit enumeration of adjacent vertices.     

Aggregating courier deliveries

We consider the problem of efficiently scheduling deliveries by an uncapacitated courier from a central location under online arrivals. We consider both adversary‐controlled and Poisson arrival processes. In the adversarial setting we provide a randomized (3βΔ/2δ ? 1) ‐competitive algorithm, where β is the approximation ratio of the traveling salesman problem, δ is the minimum distance between the central location and any customer, and Δ is the length of the optimal traveling salesman tour overall customer locations and the central location. We provide instances showing that this analysis is tight. We also prove a 1 + 0.271Δ/δ lower‐bound on the competitive ratio of any algorithm in this setting. In the Poisson setting, we relax our assumption of deterministic travel times by assuming that travel times are distributed with a mean equal to the excursion length. We prove that optimal policies in this setting follow a threshold structure and describe this structure. For the half‐line metric space we bound the performance of the randomized algorithm in the Poisson setting, and show through numerical experiments that the performance of the algorithm is often much better than this bound.