Expected waiting time rankings in extended machine-repair models

The present paper studies the relative magnitudes of expected waiting times in extended machine-repair models, when processing times are of two Erlang types. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 864–870, 1999     

The impact of exponential smoothing forecasts on the bullwhip effect

An important phenomenon often observed in supply chain management, known as the bullwhip effect, implies that demand variability increases as one moves up the supply chain, i.e., as one moves away from customer demand. In this paper we quantify this effect for simple, two‐stage, supply chains consisting of a single retailer and a single manufacturer. We demonstrate that the use of an exponential smoothing forecast by the retailer can cause the bullwhip effect and contrast these results with the increase in variability due to the use of a moving average forecast. We consider two types of demand processes, a correlated demand process and a demand process with a linear trend. We then discuss several important managerial insights that can be drawn from this research. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 269–286, 2000     

On scheduling with ready-times,due-dates and vacations

A single machine sequencing problem is considered in which there are ready-time and due-date constraints on jobs and vacation constraints on the machine. Each vacation has fixed starting and finish time and no preemption is allowed for the jobs. The objective is to minimize maximum lateness. An intriguing feature of this formulation is that it allows sequencing in disconnected time windows. A relaxation of the problem is obtained by modeling the vacations as a set of jobs with flexible ready-times and artificial due-dates and a branch and bound algorithm is developed for the problem. In the algorithm, the search is not only guided by the bounds but also by a careful manipulation of the artificial due-dates. Consequently; while searching in the relaxed solution space, solutions of the original problem are implicitly enumerated. Computational results indicate that the algorithm can satisfactorily solve problems with multiple vacations.     

When is greedy module assembly optimal?

Many coherent systems are configurations of identically structured modules, each consisting of a number of different components. The objective is to assemble the modules out of a collection of available components, and to install the modules in the system in a way that maximizes reliability. The greedy assembly rule builds one module out of the best available components, another out of the best remaining components, and so on. This article shows that greedy assembly is optimal whenever the modules have a series structure, no matter what the structure of the system in which the modules will be used might be, provided that the modules, once assembled, are installed in the system in an optimal way. The article also demonstrates that series modules are unique in this regard.     

The value of information sharing in a two‐stage supply chain with production capacity constraints

We consider a simple two‐stage supply chain with a single retailer facing i.i.d. demand and a single manufacturer with finite production capacity. We analyze the value of information sharing between the retailer and the manufacturer over a finite time horizon. In our model, the manufacturer receives demand information from the retailer even during time periods in which the retailer does not order. To analyze the impact of information sharing, we consider the following three strategies: (1) the retailer does not share demand information with the manufacturer; (2) the retailer does share demand information with the manufacturer and the manufacturer uses the optimal policy to schedule production; (3) the retailer shares demand information with the manufacturer and the manufacturer uses a greedy policy to schedule production. These strategies allow us to study the impact of information sharing on the manufacturer as a function of the production capacity, and the frequency and timing in which demand information is shared. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

Approximation algorithms for general one‐warehouse multi‐retailer systems

Logistical planning problems are complicated in practice because planners have to deal with the challenges of demand planning and supply replenishment, while taking into account the issues of (i) inventory perishability and storage charges, (ii) management of backlog and/or lost sales, and (iii) cost saving opportunities due to economies of scale in order replenishment and transportation. It is therefore not surprising that many logistical planning problems are computationally difficult, and finding a good solution to these problems necessitates the development of many ad hoc algorithmic procedures to address various features of the planning problems. In this article, we identify simple conditions and structural properties associated with these logistical planning problems in which the warehouse is managed as a cross‐docking facility. Despite the nonlinear cost structures in the problems, we show that a solution that is within ε‐optimality can be obtained by solving a related piece‐wise linear concave cost multi‐commodity network flow problem. An immediate consequence of this result is that certain classes of logistical planning problems can be approximated by a factor of (1 + ε) in polynomial time. This significantly improves upon the results found in literature for these classes of problems. We also show that the piece‐wise linear concave cost network flow problem can be approximated to within a logarithmic factor via a large scale linear programming relaxation. We use polymatroidal constraints to capture the piece‐wise concavity feature of the cost functions. This gives rise to a unified and generic LP‐based approach for a large class of complicated logistical planning problems. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009     

Beyond Just War: Military Strategy for the Common Good

The objective of this article is to move ethical discourse on military strategy beyond the confines of the established War Convention. This is achieved by utilising the common good, a concept found in political philosophy and theology. The common good acts as a positive organising concept for socio-political activity. With its focus on peace, development and the flourishing of the individual and community, the common good poses a significant challenge to strategy. This article constructs an approach to strategy that is compatible with the common good. Importantly, it does so whilst respecting the pursuit of victory as an indispensable component of strategy’s true nature. The theory presented in this article is then tested in relation to four different modes of strategy: regular war, irregular war, deterrence, and cyberwar.