Evaluating the Spillover Effects of the Colombian Conflict in Ecuador

The Colombian civil war lasted for nearly six decades with approximately 10 percent of its population being displaced over the same period. The implications of this conflict have transgressed international boundaries. Countries such as Ecuador experienced an exodus of victims as well as an increase in the presence of armed groups, along with the proliferation of illegal businesses. Even though the internal social and economic consequences of the Colombian conflict have been documented in the literature, there is yet to be a study addressing these issues from the perspective of impacted neighboring countries. In this work, we contribute to the literature by evaluating whether the influx of asylum seekers and the increasing presence of armed groups in the bordering provinces of Ecuador have lead to an increase in violence among these provinces. We do not find any link between the arrival of asylum seekers and the incidence of violent crimes in the Ecuadorean bordering provinces. Similarly, our results indicate that despite an increase in the presence of armed groups, these regions did not experience an increase in the homicide rates significantly different from the other provinces. The results are robust to various specifications and econometric techniques.     

Buying Peace? Civil War Peace Duration and Private Military & Security Companies

Do Private Military and Security Companies (PMSCs) impact peace duration after civil war? I argue that the role these organisations play in a conflict can impact post-conflict stability. Specifically, I suggest that variance in services provided by PMSCs can influence rebels’ calculations about relative capabilities. These calculations then contribute to the probability for civil war recurrence. Building on the bargaining framework, with a focus on information and commitment problems, this article demonstrates that PMSCs participating in armed combat operations can jeopardise the stability of peace following civil war. Three case narratives (Angola, Sierra Leone and Croatia) are used to probe the theoretical argument and results are illustrative – PMSCs serving as force multipliers contribute to an increase in the probability for conflict recurrence.     

Algorithm to solve a chance‐constrained network capacity design problem with stochastic demands and finite support

We consider the problem of determining the capacity to assign to each arc in a given network, subject to uncertainty in the supply and/or demand of each node. This design problem underlies many real‐world applications, such as the design of power transmission and telecommunications networks. We first consider the case where a set of supply/demand scenarios are provided, and we must determine the minimum‐cost set of arc capacities such that a feasible flow exists for each scenario. We briefly review existing theoretical approaches to solving this problem and explore implementation strategies to reduce run times. With this as a foundation, our primary focus is on a chance‐constrained version of the problem in which α% of the scenarios must be feasible under the chosen capacity, where α is a user‐defined parameter and the specific scenarios to be satisfied are not predetermined. We describe an algorithm which utilizes a separation routine for identifying violated cut‐sets which can solve the problem to optimality, and we present computational results. We also present a novel greedy algorithm, our primary contribution, which can be used to solve for a high quality heuristic solution. We present computational analysis to evaluate the performance of our proposed approaches. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 236–246, 2016     

Northern Ireland and minimum force: the refutation of a concept?

The debate over whether there exists a British counter-insurgency tradition of minimum force is one that has been thoroughly discussed. Is there anything left to say? This study suggests there is further insight to be attained if one explicitly evaluates the concept of minimum force in relation to the conduct of the security forces in the years of the Northern Ireland conflict. Through an examination of three key periods in the conflict, it will be shown that while there was invariably an awareness of the need to act with restraint among senior officers at the strategic level, this was often difficult to apply at the tactical level in the heat of confrontation. The argument demonstrates that the British Army, and other instruments of the state, rarely acted in a manner that could be described as ‘minimal’. Instead, it was the broader liberal values of the British state that explains largely the degrees of restraint exhibited by the government and security forces.     

Bayesian inference for a Lanchester type combat model

We undertake inference for a stochastic form of the Lanchester combat model. In particular, given battle data, we assess the type of battle that occurred and whether or not it makes any difference to the number of casualties if an army is attacking or defending. Our approach is Bayesian and we use modern computational techniques to fit the model. We illustrate our method using data from the Ardennes campaign. We compare our results with previous analyses of these data by Bracken and Fricker. Our conclusions are somewhat different to those of Bracken. Where he suggests that a linear law is appropriate, we show that the logarithmic or linear‐logarithmic laws fit better. We note however that the basic Lanchester modeling assumptions do not hold for the Ardennes data. Using Fricker's modified data, we show that although his “super‐logarithmic” law fits best, the linear, linear‐logarithmic, and logarithmic laws cannot be ruled out. We suggest that Bayesian methods can be used to make inference for battles in progress. We point out a number of advantages: Prior information from experts or previous battles can be incorporated; predictions of future casualties are easily made; more complex models can be analysed using stochastic simulation techniques. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 541–558, 2000     

Scheduling customer arrivals to a stochastic service system

An efficient algorithm for determining the optimal arrival schedule for customers in a stochastic service system is developed. All customers arrive exactly when scheduled, and service times are modeled as iid Erlang random variables. Costs are incurred at a fixed rate per unit of time each customer waits for service, and an additional cost is incurred for every unit of time the server operates beyond a scheduled closing time. The objective is to minimize total operating cost. This type of problem arises in many operational contexts including transportation, manufacturing, and appointment‐based services. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 549–559, 1999     

The open shop scheduling problem with a given sequence of jobs on one machine

The paper considers the open shop scheduling problem to minimize the make-span, provided that one of the machines has to process the jobs according to a given sequence. We show that in the preemptive case the problem is polynomially solvable for an arbitrary number of machines. If preemption is not allowed, the problem is NP-hard in the strong sense if the number of machines is variable, and is NP-hard in the ordinary sense in the case of two machines. For the latter case we give a heuristic algorithm that runs in linear time and produces a schedule with the makespan that is at most 5/4 times the optimal value. We also show that the two-machine problem in the nonpreemptive case is solvable in pseudopolynomial time by a dynamic programming algorithm, and that the algorithm can be converted into a fully polynomial approximation scheme. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 705–731, 1998     

Optimization in simulation: Current issues and the future outlook

Simulation is commonly used to find the best values of decision variables for problems which defy analytical solutions. This objective is similar to that of optimization problems and thus, mathematical programming techniques may be applied to simulation. However, the application of mathematical programming techniques, e.g., the gradient methods, to simulation is compounded by the random nature of simulation responses and by the complexity of the statistical issues involved. The literature relevant to optimization in simulation is scattered, and no comprehensive and up-to-date treatment of the subject is presently available. To that end, this article brings together numerous concepts related to t he problem of optimization in simulation. Specifically, it discusses the application of mathematical programming techniques to optimization in simulation, response surface methodology and designs, perturbation analysis, and frequency domain simulation experiments. The article provides a user with an overview of the available optimization techniues and identifies future research possibilities.     

A guarantee rate optimization model for wastewater treatment system design under uncertainty

We consider a design problem for wastewater treatment systems that considers uncertainty in pollutant concentration levels at water sources. The goal is to optimize the selection of treatment technologies and pipeline connections, so that treated wastewater can achieve specified effluents discharge limits as well as possible. We propose a new two-stage model to optimize a set of guarantee levels, that is, the maximum concentration level of source pollutants for which treated wastewater can be compliant with discharge limits. In the first stage, treatment technologies and pipeline connections are selected. In the second stage, when pollutant concentration levels are revealed, wastewater distribution and mixing are determined. A key attractiveness of the proposed guarantee rate optimization model is that it can be simplified into a single-stage mixed-integer linear program. In our numerical experiments based on real-world pollutants data, the guarantee rate model demonstrates its advantages in terms of computational efficiency, scalability and solution quality, compared with the standard probability maximization model. Finally, the methodology proposed in this paper can also be applied to other two-stage problems under uncertainty with similar uncertainty characteristics.     

Forces of heresy versus forces of conservation: making sense of Hezb-e Islami-ye Afghanistan’s and the Taleban’s positions in the Afghan insurgency

Ethnicity and ideology are frequently used to determine whether an armed group is hostile or friendly vis-à-vis the state. By contrast, I argue that the social structure of insurgent movements holds more explanatory power for their respective positions than ethnicity or ideology. To illustrate this, I apply Pierre Bourdieu’s concept of a contest between forces of ‘conservation’ and forces of ‘heresy’ to the current Afghanistan war. I demonstrate that the social structure of the Taleban renders them prone to ‘heresy’, while the formerly second biggest insurgent group, Gulbuddin Hekmatyar’s party, has rather been an impeded force of ‘conservation.’