Leaderless Global Jihadism: The Paradox of Discriminate Violence

Jihadist violence is typically associated with being particularly indiscriminate. Often, as in variations of the ‘new terrorism’ thesis, this characteristic is proposed to correspond in some way to its other attributes such as its globalised, decentralised and ‘postmodern’ religious nature. Recent work appears to give more substance to such claims, by claiming to show a relationship between indiscriminate violence and decentralised group organisation. However, in this paper we show, based on an analysis of jihadist targeting in Western Europe and America from 2001 to 2013, that targeting choices by jihadists unconnected to organised militant groups have in fact been consistently more, rather than less discriminate in their targeting choices than their better-integrated peers. Drawing on this finding, as well as a broader reading of jihadist targeting discourses, we argue for a more complex understanding of the relationship between radicalisation, extremist ideology, decentralisation, and targeting choice.     

Schedule design for liner services under vessel speed reduction incentive programs

Gas and particulate emissions from ship transportation have been increasing in recent years. In order to mitigate ship emissions near coastal areas, voluntary vessel speed reduction incentive programs (VSRIPs) were put in place by a number of ports. This paper studies a schedule design problem faced by liner shipping companies under VSRIPs. It proposes a mixed-integer nonlinear mathematical model for the minimization of the total cost, consisting of fuel cost, as well as operating cost, minus dockage refunds. The model balances three determinants, that is, the compliance of VSRIPs, the speed limit (the maximum physical speed of ships and the upper speed limit imposed by VSRIPs), and the limited number of ships. An enumerative algorithm and a piecewise-linear approximation algorithm are developed, based on some properties of the nonlinear model. The efficiency of the proposed algorithms is validated through extensive computational experiments.     

Clustered coverage orienteering problem of unmanned surface vehicles for water sampling

This study investigates a clustered coverage orienteering problem (CCOP), which is a generalization of the classical orienteering problem. The problem is widely motivated by the emerging unmanned techniques (eg, unmanned surface vehicles and drones) applied to environmental monitoring. Specifically, the unmanned surface vehicles (USVs) are used to monitor reservoir water quality by collecting samples. In the CCOP, the water sampling sites (ie, the nodes) are grouped into clusters, and a minimum number of nodes must be visited in each cluster. With each node representing a certain coverage area of the water, the objective of the CCOP is to monitor as much as possible the total coverage area in one tour of the USV, considering that overlapping areas provide no additional information. An integer programming model is first formulated through a linearization procedure that captures the overlapping feature. A two-stage exact algorithm is proposed to obtain an optimal solution to the problem. The efficiency and effectiveness of the two-stage exact algorithm are demonstrated through experiments on randomly generated instances. The algorithm can effectively solve instances with up to 60 sampling sites.     

Scheduling and lot streaming in two‐machine open shops with no‐wait in process

We study the problem of minimizing the makespan in no‐wait two‐machine open shops producing multiple products using lot streaming. In no‐wait open shop scheduling, sublot sizes are necessarily consistent; i.e., they remain the same over all machines. This intractable problem requires finding sublot sizes, a product sequence for each machine, and a machine sequence for each product. We develop a dynamic programming algorithm to generate all the dominant schedule profiles for each product that are required to formulate the open shop problem as a generalized traveling salesman problem. This problem is equivalent to a classical traveling salesman problem with a pseudopolynomial number of cities. We develop and test a computationally efficient heuristic for the open shop problem. Our results indicate that solutions can quickly be found for two machine open shops with up to 50 products. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005     

The strategic effects of a merger upon supplier interactions

We consider how a merger between two naturally differentiated dealers affects their interactions with a common supplier and identify conditions under which the merger can increase or decrease the combined net worth of the two firms. Among other things, we find that the attractiveness of merging depends upon the extent to which end demand can be stimulated by either an upstream supplier or the dealers. Specifically, the greater the supplier's ability to invest in stimulating end demand, the more likely it is that the naturally differentiated firms will be better off operating independently than merging. On the other hand, if the greatest opportunities for stimulating demand are through the service that is provided by the dealers, then merging their operations will be more attractive. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Scheduling twin robots on a line

This article introduces the twin robots scheduling problem (TRSP), in which two robots positioned at the opposite ends of a rail are required to deliver items to positions along the rail, and the objective is to minimize the makespan. A proof of ‐hardness of the TRSP is presented, along with exact and heuristic algorithms. Computational results on challenging instances are provided.Copyright © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 119–130, 2014     

A branch‐and‐cut algorithm for the quay crane scheduling problem in a container terminal

The quay crane scheduling problem consists of determining a sequence of unloading and loading movements for cranes assigned to a vessel in order to minimize the vessel completion time as well as the crane idle times. Idle times originate from interferences between cranes since these roll on the same rails and a minimum safety distance must be maintained between them. The productivity of container terminals is often measured in terms of the time necessary to load and unload vessels by quay cranes, which are the most important and expensive equipment used in ports. We formulate the quay crane scheduling problem as a vehicle routing problem with side constraints, including precedence relationships between vertices. For small size instances our formulation can be solved by CPLEX. For larger ones we have developed a branch‐and‐cut algorithm incorporating several families of valid inequalities, which exploit the precedence constraints between vertices. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

What you should know about the vehicle routing problem

In the Vehicle Routing Problem (VRP), the aim is to design a set of m minimum cost vehicle routes through n customer locations, so that each route starts and ends at a common location and some side constraints are satisfied. Common applications arise in newspaper and food delivery, and in milk collection. This article summarizes the main known results for the classical VRP in which only vehicle capacity constraints are present. The article is structured around three main headings: exact algorithms, classical heuristics, and metaheuristics. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

A branch‐and‐cut algorithm for the nonpreemptive swapping problem

In the Swapping Problem (SP), we are given a complete graph, a set of object types, and a vehicle of unit capacity. An initial state specifies the object type currently located at each vertex (at most one type per vertex). A final state describes where these object types must be repositioned. In general, there exist several identical objects for a given object type, yielding multiple possible destinations for each object. The SP consists of finding a shortest vehicle route starting and ending at an arbitrary vertex, in such a way that each object is repositioned in its final state. This article exhibits some structural properties of optimal solutions and proposes a branch‐and‐cut algorithm based on a 0‐1 formulation of the problem. Computational results on random instances containing up to 200 vertices and eight object types are reported. © 2009 Wiley Periodicals, Inc. Naval Research Logistics 2009