Optimal betting strategies for favorable games

We examine the problem of a gambler interested in maximizing the expected value of a convex utility function of his fortune after n plays of a game. We allow any probability distribution to rule the outcome of each play, and this distribution may change from play to play according to a Markov process. We present results regarding the existence of an optimal policy and its structural dependence on the gambler's fortune. The well-known results of Bellman and Kalaba for exponential and logarithmic utility functions and coin-tossing games are generalized. We also examine the situation of general stale spaces and show that the same structural results hold.     

Computation techniques for large scale undiscounted markov decision processes

In this paper we consider computation techniques associated with the optimization of large scale Markov decision processes. Markov decision processes and the successive approximation procedure of White are described. Then a procedure for scaling continuous time and renewal processes so that they are amenable to the White procedure is discussed. The effect of the scale factor value on the convergence rate of the procedure and insights into proper scale factor selection are given.     

The many-product cargo loading problem

An algorithm, based upon dynamic programming, is developed for a class of fixed-cost cargo loading problems. The problems can be formulated as integer programming problems, but cannot be efficiently solved as such because of computational difficulties. The algorithm developed has proved to be very efficient in an actual operations research study involving over 500 different cargo items, more than 40 possible stops and several types of transportation vehicles. A numerical illustration is provided.     

Cyclic best first search: Using contours to guide branch‐and‐bound algorithms

The cyclic best‐first search (CBFS) strategy is a recent search strategy that has been successfully applied to branch‐and‐bound algorithms in a number of different settings. CBFS is a modification of best‐first search (BFS) that places search tree subproblems into contours which are collections of subproblems grouped in some way, and repeatedly cycles through all non‐empty contours, selecting one subproblem to explore from each. In this article, the theoretical properties of CBFS are analyzed for the first time. CBFS is proved to be a generalization of all other search strategies by using a contour definition that explores the same sequence of subproblems as any other search strategy. Further, a bound is proved between the number of subproblems explored by BFS and the number of children generated by CBFS, given a fixed branching strategy and set of pruning rules. Finally, a discussion of heuristic contour‐labeling functions is provided, and proof‐of‐concept computational results for mixed‐integer programming problems from the MIPLIB 2010 database are shown. © 2017 Wiley Periodicals, Inc. Naval Research Logistics, 64: 64–82, 2017     

Augmented nested sampling for stochastic programs with recourse and endogenous uncertainty

We propose a novel simulation‐based approach for solving two‐stage stochastic programs with recourse and endogenous (decision dependent) uncertainty. The proposed augmented nested sampling approach recasts the stochastic optimization problem as a simulation problem by treating the decision variables as random. The optimal decision is obtained via the mode of the augmented probability model. We illustrate our methodology on a newsvendor problem with stock‐dependent uncertain demand both in single and multi‐item (news‐stand) cases. We provide performance comparisons with Markov chain Monte Carlo and traditional Monte Carlo simulation‐based optimization schemes. Finally, we conclude with directions for future research.     

Exact algorithms and bounds for the dynamic assignment interdiction problem

We study a multi‐stage dynamic assignment interdiction (DAI) game in which two agents, a user and an attacker, compete in the underlying bipartite assignment graph. The user wishes to assign a set of tasks at the minimum cost, and the attacker seeks to interdict a subset of arcs to maximize the user's objective. The user assigns exactly one task per stage, and the assignment costs and interdiction impacts vary across stages. Before any stage commences in the game, the attacker can interdict arcs subject to a cardinality constraint. An interdicted arc can still be used by the user, but at an increased assignment cost. The goal is to find an optimal sequence of assignments, coupled with the attacker's optimal interdiction strategy. We prove that this problem is strongly NP‐hard, even when the attacker can interdict only one arc. We propose an exact exponential‐state dynamic‐programming algorithm for this problem as well as lower and upper bounds on the optimal objective function value. Our bounds are based on classical interdiction and robust optimization models, and on variations of the DAI game. We examine the efficiency of our algorithms and the quality of our bounds on a set of randomly generated instances. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 373–387, 2017     

All Counterinsurgency is Local: Counterinsurgency and Rebel Legitimacy

Abstract

Although the concept of legitimacy is central to Western counterinsurgency theory, most discourse in this area black-boxes the concept. It hence remains under-specified in many discussions of counterinsurgency. Fortunately, recent research on rebel governance and legitimacy contributes to our understanding of the problems faced by counterinsurgents who want to boost state legitimacy while undermining that of the rebels. Taken together, this research illustrates that a rational choice approach to legitimacy is simplistic; that micro-level factors ultimately drive legitimacy dynamics; and that both cooption of existing legitimate local elites and their replacement from the top–down is unlikely to succeed. Western counterinsurgency doctrine has failed to grasp the difficulties this poses for it.     

Dangerous work: Terrorism against U.S. diplomats

The goal of diplomats is to represent their countries’ interests through diplomacy, not arms. Because they are not military personnel, they may be perceived as at lower risk of being the target of terrorists. However, recent events have called this perception into question. Despite this danger, there has been little research on terrorist attacks against diplomats. Drawing on the terrorism studies literature, this article argues that diplomats are targeted more than non-diplomatic targets in countries where certain U.S. foreign policies are implemented. An empirical analysis of 471 attacks against U.S. diplomats from 1970 to 2011 reveals that while U.S. alliances and foreign aid increase the likelihood of attacks against diplomats, U.S. military intervention and civil war, on the other hand, increase the risk of terrorism against non-diplomatic targets. This finding is relevant because it shows terrorist attacks against diplomats result from certain types of foreign policy.     

The US NATO and military burden sharing: post-Cold War accomplishments and future prospects

NATO burden sharing has become an especially timely issue in the past several years as a result of a number of factors, including Russian annexation of Crimea and destabilization of eastern Ukraine in 2014. This article argues that alliance unity among the great democracies of Europe and North America is indispensable to peace and stability on the Eurasian continent. A fractured NATO, and especially, a large divide in purposes or commitments as between the United States and its European security partners, invites aggression and the possibility of inadvertent escalation. Past successes and failures in US-involved multinational peace and stability operations, within and outside of Europe, show that mission accomplishment requires give and take, including the occasional acceptance of unequal costs and benefits among the members, in order to achieve peace and security objectives.