Adjacency‐based local top‐down search method for finding maximal efficient faces in multiple objective linear programming

It is well‐known that the efficient set of a multiobjective linear programming (MOLP) problem can be represented as a union of the maximal efficient faces of the feasible region. In this paper, we propose a method for finding all maximal efficient faces for an MOLP. The new method is based on a condition that all efficient vertices (short for the efficient extreme points and rays) for the MOLP have been found and it relies on the adjacency, affine independence and convexity results of efficient sets. The method uses a local top‐down search strategy to determine maximal efficient faces incident to every efficient vertex for finding maximal efficient faces of an MOLP problem. To our knowledge, the proposed method is the first top‐down search method that uses the adjacency property of the efficient set to find all maximal efficient faces. We discuss this and other advantages and disadvantages of the algorithm. We also discuss some computational experience we have had with our computer code for implementing the algorithm. This computational experience involved solving several MOLP problems with the code.     

Security sector reform,ethnic representation and perceptions of safety: evidence from Kosovo

This article explores the relationship between ethnic representation in security sector institutions and perceptions of safety. While most studies on post-conflict institutional reform focus on national institutions and outcomes, this article argues that a more nuanced view on ethnic representation is fruitful in order to account for the everyday perceptions of local people. Drawing on post-conflict Kosovo, the article analyzes how the representation of ethnic minorities in security institutions affects perceptions of safety among individuals across Kosovo’s municipalities. It also analyzes original interview data collected in the Pristina and Mitrovica municipalities that are typical cases of our sample. Both approaches validate that those municipalities that have ethnically representative security institutions also have higher levels of perceived safety.     

An integer decomposition algorithm for solving a two‐stage facility location problem with second‐stage activation costs

We study a stochastic scenario‐based facility location problem arising in situations when facilities must first be located, then activated in a particular scenario before they can be used to satisfy scenario demands. Unlike typical facility location problems, fixed charges arise in the initial location of the facilities, and then in the activation of located facilities. The first‐stage variables in our problem are the traditional binary facility‐location variables, whereas the second‐stage variables involve a mix of binary facility‐activation variables and continuous flow variables. Benders decomposition is not applicable for these problems due to the presence of the second‐stage integer activation variables. Instead, we derive cutting planes tailored to the problem under investigation from recourse solution data. These cutting planes are derived by solving a series of specialized shortest path problems based on a modified residual graph from the recourse solution, and are tighter than the general cuts established by Laporte and Louveaux for two‐stage binary programming problems. We demonstrate the computational efficacy of our approach on a variety of randomly generated test problems. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

Optimal sample size allocation for tests with multiple levels of stress with extreme value regression

In this article, we discuss the optimal allocation problem in a multiple stress levels life‐testing experiment when an extreme value regression model is used for statistical analysis. We derive the maximum likelihood estimators, the Fisher information, and the asymptotic variance–covariance matrix of the maximum likelihood estimators. Three optimality criteria are defined and the optimal allocation of units for two‐ and k‐stress level situations are determined. We demonstrate the efficiency of the optimal allocation of units in a multiple stress levels life‐testing experiment by using real experimental situations discussed earlier by McCool and Nelson and Meeker. Monte Carlo simulations are used to show that the optimality results hold for small sample sizes as well. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Supply licensing when the manufacturer strategically commits to invest in R&D

This article proposes a strategic reason for a proprietary component supplier to license her technology to a competitor or a manufacturer: her anticipation of the manufacturer's strategic commitment to invest in research and development (R&D). We address this phenomenon with a game theoretic model. Our results show that the manufacturer's full commitment to invest in R&D enables the supplier to license, sell a larger quantity through the supply chain, and charge lower prices. These results are robust to the type of demand uncertainty faced by the manufacturer within the class of increasing generalized failure rate distributions. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 341–350, 2014     

Limiting survival functions of self‐similar structures

We show the existence of a unique analytic single parameter limiting survival function arising from the repeated composition of a coherent structure as the number of components tends to infinity. Examples include the repeated composition process of the bridge structure. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2004.     

The “motivated bias” dilemma in warfare and intelligence

The goal of this article is to challenge the assumption of rationality in the behavior of decision-making units involved in security, defense, intelligence and warfare and to consider the influence of “motivated bias” in such instances. A review of motivational literature within international politics and a discussion of literature applying “motivated biases” to warfare and strategic surprise will offer an alternative view of the primacy of rationality in such decisions.