New heuristic methods for the capacitated multi‐facility Weber problem

In this paper we consider the capacitated multi‐facility Weber problem with the Euclidean, squared Euclidean, and ?_p‐distances. This problem is concerned with locating m capacitated facilities in the Euclidean plane to satisfy the demand of n customers with the minimum total transportation cost. The demand and location of each customer are known a priori and the transportation cost between customers and facilities is proportional to the distance between them. We first present a mixed integer linear programming approximation of the problem. We then propose new heuristic solution methods based on this approximation. Computational results on benchmark instances indicate that the new methods are both accurate and efficient. © 2006 Wiley Periodicals, Inc. Naval Research Logistics 2006     

Constructing a strict total order for alternatives characterized by multiple criteria: An extension

The problem of finding a strict total order for a finite set of multiple criteria alternatives is considered. Our research extends previous work by us, which considered finding a partial order for a finite set of alternatives. We merge the preference information extracted from the preference cones and corresponding polyhedral sets, with the information derived from pairwise comparisons of two alternatives, yielding a preference matrix. This preference matrix is used as input to an integer programming model to obtain a strict total order that provides a transitive ranking for the set of alternatives. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 155–163, 2014     

THE PEACE DIVIDEND EFFECT OF TURKISH CONVERGENCE TO THE EU: A MULTI‐REGION DYNAMIC CGE MODEL ANALYSIS FOR GREECE AND TURKEY

This paper examines the peace dividend effect of Turkish convergence to EU membership. By employing a multi‐region dynamic CGE model, we examine the prospect for conflict resolution if Turkey becomes an EU member. The model allows us to analyse several scenarios that imply varying amounts of reduction of the military expenditure/GDP ratios. On the one hand, this change will cause a decrease in sectoral demand for military expenditures, while on the other hand, reallocation of the reduced expenditure on (i) education, (ii) tax decrease, and (iii) infrastructure, should have a huge growth impact. Our dynamic CGE simulation experiments emphasize the economic gain for all parties involved.     

Asymmetric effects of military expenditure between Turkey and Greece

One of the major topics of the defense economics literature regarding Turkey and Greece has been the empirical modeling of various aspects of arms racing. However, despite a considerable amount of research, little evidence has been found in favor of an arms race between the two countries. In the literature, this failure of applied studies has been attributed, among other reasons, to the sensitivity of the results to the underlying model specification, to small sample size, and to measurement issues. This study uses novel, nonlinear, models to investigate the possible relationship between the military expenditures of the two countries. It is assumed that if there are two regimes characterizing the low (or negative) and high-growth military expenditure periods, the growth rates of one country's military expenditure may have distinct effects on the military expenditure regimes of the other country or may contribute to the change from one regime to another. The nonlinear models examined are Smooth Transition Regression models (STRs). Strong evidence of nonlinearity for Greece is found, with asymmetry relating to two distinct regimes through lagged Turkish military expenditure changes.     

Automated integration of real-time and non-real-time defense systems

Various application domains require the integration of distributed real-time or near-real-time systems with non-real-time systems.Smart cities,smart homes,ambient intelligent systems,or network-centric defense systems are among these application domains.Data Distribution Service(DDS)is a communi-cation mechanism based on Data-Centric Publish-Subscribe(DCPS)model.It is used for distributed systems with real-time operational constraints.Java Message Service(JMS)is a messaging standard for enterprise systems using Service Oriented Architecture(SOA)for non-real-time operations.JMS allows Java programs to exchange messages in a loosely coupled fashion.JMS also supports sending and receiving messages using a messaging queue and a publish-subscribe interface.In this article,we pro-pose an architecture enabling the automated integration of distributed real-time and non-real-time systems.We test our proposed architecture using a distributed Command,Control,Communications,Computers,and Intelligence(C4I)system.The system has DDS-based real-time Combat Management System components deployed to naval warships,and SOA-based non-real-time Command and Control components used at headquarters.The proposed solution enables the exchange of data between these two systems efficiently.We compare the proposed solution with a similar study.Our solution is superior in terms of automation support,ease of implementation,scalability,and performance.     

Transformations of node‐balanced routing problems

This article describes a polynomial transformation for a class of unit‐demand vehicle routing problems, named node‐balanced routing problems (BRP), where the number of nodes on each route is restricted to be in an interval such that the workload across the routes is balanced. The transformation is general in that it can be applied to single or multiple depot, homogeneous or heterogeneous fleet BRPs, and any combination thereof. At the heart of the procedure lies transforming the BRP into a generalized traveling salesman problem (TSP), which can then be transformed into a TSP. The transformed graph exhibits special properties which can be exploited to significantly reduce the number of arcs, and used to construct a formulation for the resulting TSP that amounts to no more than that of a constrained assignment problem. Computational results on a number of instances are presented. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 370–387, 2015     

Reformulating linear programs with transportation constraints—With applications to workforce scheduling

We study linear programming models that contain transportation constraints in their formulation. Typically, these models have a multistage nature and the transportation constraints together with the associated flow variables are used to achieve consistency between consecutive stages. We describe how to reformulate these models by projecting out the flow variables. The reformulation can be more desirable since it has fewer variables and can be solved faster. We apply these ideas to reformulate two well‐known workforce staffing and scheduling problems: the shift scheduling problem and the tour scheduling problem. We also present computational results. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2004.     

A branch and bound algorithm for sector allocation of a naval task group

A naval task group (TG) is a collection of naval combatants and auxiliaries that are grouped together for the accomplishment of one or more missions. Ships forming a TG are located in predefined sectors. We define determination of ship sector locations to provide a robust air defense formation as the sector allocation problem (SAP). A robust formation is one that is very effective against a variety of attack scenarios but not necessarily the most effective against any scenario. We propose a 0‐1 integer linear programming formulation for SAP. The model takes the size and the direction of threat into account as well as the defensive weapons of the naval TG. We develop tight lower and upper bounds by incorporating some valid inequalities and use a branch and bound algorithm to exactly solve SAP. We report computational results that demonstrate the effectiveness of the proposed solution approach. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

An integer programming model for the weekly tour scheduling problem

We study a workforce planning and scheduling problem in which weekly tours of agents must be designed. Our motivation for this study comes from a call center application where agents serve customers in response to incoming phone calls. Similar to many other applications in the services industry, the demand for service in call centers varies significantly within a day and among days of the week. In our model, a weekly tour of an agent consists of five daily shifts and two days off, where daily shifts within a tour may be different from each other. The starting times of any two consecutive shifts, however, may not differ by more than a specified bound. Furthermore, a tour must also satisfy constraints regarding the days off, for example, it may be required that one of the days off is on a weekend day. The objective is to determine a collection of weekly tours that satisfy the demand for agents' services, while minimizing the total labor cost of the workforce. We describe an integer programming model where a weekly tour is obtained by combining seven daily shift scheduling models and days‐off constraints in a network flow framework. The model is flexible and can accommodate different daily models with varying levels of detail. It readily handles different days‐off rules and constraints regarding start time differentials in consecutive days. Computational results are also presented. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 607–624, 2001.     

Testing of software with an operational profile

One of the important features of any software system is its operational profile. This is simply the set of all operations that a software is designed to perform and the occurence probabilities of these operations. We present a new model on optimal software testing such that testing is done sequentially using a set of test cases. There may be failures due to the operations in each of these cases. The model parameters, consisting of testing costs and failure rates, all depend on the cases used and the operations performed. Our aim is to find the optimal testing durations in all of the cases in order to minimize the total expected cost. This problem leads to interesting decision models involving nonlinear programming formulations that possess explicit analytical solutions under reasonable assumptions. © 2000 John Wiley & Sons, Inc., Naval Research Logistics 47: 620–634, 2000