How do wars end? A multidisciplinary enquiry

ABSTRACT

The cessation of military confrontations rarely coincides with the end of war. Legal and political matters continue after the last shot has been fired, civilians driven from their homes try to rebuild their houses and their lives, veterans need to adapt to their new role in civil society, and the struggle to define the history and the significance of past events only begins. In recent years, in particular, the changes in the character of contemporary warfare have created uncertainties across different disciplines about how to identify and conceptualise the end of war. It is therefore an opportune moment to examine how wars end from a multidisciplinary perspective that combines enquiries into the politics of war, the laws of war and the military and intellectual history of war. This approach enables both an understanding of how ‘the end’ as a concept informs the understanding of war in international relations, in international law and in history and a reconsideration of the nature of scientific method in the field of war studies as such.     

Using real options analysis to value reoptimization options in the shifting bottleneck heuristic

The reoptimization procedure within the shifting bottleneck (SB) involves reevaluation of all previously scheduled toolgroup subproblems at each iteration of the SB heuristic. A real options analysis (ROA) model is developed to value the option to reoptimize in the SB heuristic, such that reoptimization only occurs when it is most likely to lead to a schedule with a lower objective function. To date, all ROA models have sought to value options financially (i.e., in terms of monetary value). The ROA model developed in this paper is completely original in that it has absolutely no monetary basis. The ROA methodologies presented are shown to greatly outperform both full and no reoptimization approaches with respect to both computation time and total weighted tardiness. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

Requirements planning for modular products

The focus of this paper is on determining the requirements of different component options of a modular end‐product in an uncertain environment. We explicitly model two distinct sources of uncertainty: stochastic end‐product demand and unknown market proportions for the different product options available. Our cost minimizing model focuses on determining the optimal requirements policies for component options that meet a pre‐set service level. We show that simple common‐sense requirements policies are not generally optimal; there is a non‐linear connection between service level and component requirements that is hard to characterize without a detailed analysis. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006