Ethnicity,class, and civil war: the role of hierarchy,segmentation, and cross-cutting cleavages

Why are some countries prone to ethno-nationalist conflict, whereas others are plagued by class conflict? This is a question that has seldom been raised and rarely been examined empirically. This paper presents a social-structural theory to account for the variable incidence of these two forms of political instability. These two types of conflict result from distinct principles of group solidarity – ethnicity and class – and since each individual is simultaneously a member of an ethnic group (or many such groups) and a particular class, these two principles vary in the degree to which they are mutually exclusive or cross-cutting. The degree of economic stratification between groups and economic segmentation within them shapes the relative salience of each principle of group solidarity in any society and is associated with a characteristic form of political mobilization. In places where between-group inequalities are high, and within-group inequalities low, ethnicity should be the dominant principle of group solidarity and serve as the primary basis of group conflict. By contrast, in countries where between-group inequalities are low, and within-group inequalities high, class is more likely to serve as the dominant principle of group solidarity, and conflicts along class lines are more likely. We test these conjectures with data in over 100 countries on cross-cutting cleavages, ethnic war, and class conflict. The results are supportive of the theory, and provide evidence that how groups are stratified and segmented in societies shapes the type of civil war.     

Ordering and controlling the dimensions of strategy

Colin Gray’s dimensions of strategy, built upon the earlier work of Clausewitz and Howard, has theoretical, practical, and pedagogic value for the Strategic Studies community. This paper further develops the theory, arguing that the dimensions can be controlled or managed to improve strategic performance. The dimensions are divided into two categories: “internal” and “external” to the process of strategy. The paper describes the dynamic process by which the internal dimensions, which can be controlled, are used to exert influence over the external dimensions that are beyond the control of the strategist. It is argued that six dimensions hold the key to strategic success: politics and the five dimensions concerned with warfighting. This conclusion validates the Clausewitzian paradigm with its emphasis on policy and battle.     

Optimal resource allocation and redistribution strategy in military conflicts with Lanchester square law attrition

We address the problem of optimal decision‐making in conflicts based on Lanchester square law attrition model where a defending force needs to be partitioned optimally, and allocated to two different attacking forces of differing strengths and capabilities. We consider a resource allocation scheme called the Time Zero Allocation with Redistribution (TZAR) strategy, where allocation is followed by redistribution of defending forces, on the occurrence of certain decisive events. Unlike previous work on Lanchester attrition model based tactical decision‐making, which propose time sequential tactics through an optimal control approach, the present article focuses on obtaining simpler resource allocation tactics based on a static optimization framework, and demonstrates that the results obtained are similar to those obtained by the more complex dynamic optimal control solution. Complete solution for this strategy is obtained for optimal partitioning of resources of the defending forces. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

A stochastic air combat logistics decision model for Blue versus Red opposition

Technologically advanced aircraft rely on robust and responsive logistics systems to ensure a high state of operational readiness. This paper fills a critical gap in the literature for combat models by closely relating effectiveness of the logistics system to determinants of success in combat. We present a stochastic diffusion model of an aerial battle between Blue and Red forces. The number of aircraft of Blue forces aloft and ready to be aloft on combat missions is limited by the maximum number of assigned aircraft, the reliability of aircraft subsystems, and the logistic system's ability to repair and replenish those subsystems. Our parsimonious model can illustrate important trade‐offs between logistics decision variables and operational success.     

Heuristics for the multi‐resource generalized assignment problem

The well‐known generalized assignment problem (GAP) involves the identification of a minimum‐cost assignment of tasks to agents when each agent is constrained by a resource in limited supply. The multi‐resource generalized assignment problem (MRGAP) is the generalization of the GAP in which there are a number of different potentially constraining resources associated with each agent. This paper explores heuristic procedures for the MRGAP. We first define a three‐phase heuristic which seeks to construct a feasible solution to MRGAP and then systematically attempts to improve the solution. We then propose a modification of the heuristic for the MRGAP defined previously by Gavish and Pirkul. The third procedure is a hybrid heuristic that combines the first two heuristics, thus capturing their relative strengths. We discuss extensive computational experience with the heuristics. The hybrid procedure is seen to be extremely effective in solving MRGAPs, generating feasible solutions to more than 99% of the test problems and consistently producing near‐optimal solutions. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 468–483, 2001     

The value of information sharing in a two‐stage supply chain with production capacity constraints

We consider a simple two‐stage supply chain with a single retailer facing i.i.d. demand and a single manufacturer with finite production capacity. We analyze the value of information sharing between the retailer and the manufacturer over a finite time horizon. In our model, the manufacturer receives demand information from the retailer even during time periods in which the retailer does not order. To analyze the impact of information sharing, we consider the following three strategies: (1) the retailer does not share demand information with the manufacturer; (2) the retailer does share demand information with the manufacturer and the manufacturer uses the optimal policy to schedule production; (3) the retailer shares demand information with the manufacturer and the manufacturer uses a greedy policy to schedule production. These strategies allow us to study the impact of information sharing on the manufacturer as a function of the production capacity, and the frequency and timing in which demand information is shared. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

Modeling and analysis of uncertain time‐critical tasking problems

This paper describes modeling and operational analysis of a generic asymmetric service‐system situation in which (a) Red agents, potentially threatening, but in another but important interpretation, are isolated friendlies, such as downed pilots, that require assistance and “arrive” according to some partially known and potentially changing pattern in time and space; and (b) Reds have effectively limited unknown deadlines or times of availability for Blue service, i.e., detection, classification, and attack in a military setting or emergency assistance in others. We discuss various service options by Blue service agents and devise several approximations allowing one to compute efficiently those proportions of tasks of different classes that are successfully served or, more generally, if different rewards are associated with different classes of tasks, the percentage of the possible reward gained. We suggest heuristic policies for a Blue server to select the next task to perform and to decide how much time to allocate to that service. We discuss this for a number of specific examples. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006.