A linear programming approach to geometric programs

A cutting plane method, based on a geometric inequality, is described as a means of solving geometric programs. While the method is applied to the primal geometric program, it is shown to retain the geometric programming duality relationships. Several methods of generating the cutting planes are discussed and illustrated on some example problems.     

Minimax trees,paths, and cut sets

The notions of minimax paths, trees, and cut sets are defined for undirected graphs; and relationships between these entities are established. Simple solution procedures based on these relationships are presented.     

Toward a study of bidding processes part IV - games with unknown costs

This paper represents a continuation of three previous papers [1-.3] in the study of competitive bidding processes. It treats the case where a bidder's knowledge of his competitor's cost i s given by a probability distribution over a certain interval. The results obtained extend the work of Vickrey [4] to the case where the cost intervals a r e not necessarily symmetric.     

A tactical warfare simulation program

The Tactical Warfare Simulation Program is a procedure by which the major interactions among opposing military units and terrain features can be treated in a tactical limited warfare situation. It is a critical-area, sequence-of-event model and is programmed in SIM-SCRIPT. In this program a military unit is described by such properties as strength, size, location, velocity, and attrition rates. Some of the events which can occur to a military unit are entering/leaving terrain features, becoming engaged/disengaged with opposing units, retreating, reaching an objective, and breaking. Following a discussion of the general features of the program, a study of a hypothetical war is presented.     

Cyclic best first search: Using contours to guide branch‐and‐bound algorithms

The cyclic best‐first search (CBFS) strategy is a recent search strategy that has been successfully applied to branch‐and‐bound algorithms in a number of different settings. CBFS is a modification of best‐first search (BFS) that places search tree subproblems into contours which are collections of subproblems grouped in some way, and repeatedly cycles through all non‐empty contours, selecting one subproblem to explore from each. In this article, the theoretical properties of CBFS are analyzed for the first time. CBFS is proved to be a generalization of all other search strategies by using a contour definition that explores the same sequence of subproblems as any other search strategy. Further, a bound is proved between the number of subproblems explored by BFS and the number of children generated by CBFS, given a fixed branching strategy and set of pruning rules. Finally, a discussion of heuristic contour‐labeling functions is provided, and proof‐of‐concept computational results for mixed‐integer programming problems from the MIPLIB 2010 database are shown. © 2017 Wiley Periodicals, Inc. Naval Research Logistics, 64: 64–82, 2017     

British and German initiatives for defence cooperation: the Joint Expeditionary Force and the Framework Nations Concept

At NATO’s 2014 Wales Summit, the UK and Germany unveiled two new initiatives for European defence cooperation, known, respectively, as the Joint Expeditionary Force (JEF) and the Framework Nations Concept (FNC). Both were the result of economic pressures and the need to exercise intra-alliance leadership, but they represented very different approaches to cooperation. The JEF was to be a UK-led contingency force for short-notice operations, selectively incorporating forces from allies and partners. The FNC sought to coordinate capability development between groups of allies, centred on larger framework nations, to develop coherent capability-clusters available to meet NATO’s force requirements. The common denominator and novelty of the initiatives was the building of forces and capabilities multinationally by having major states act as framework nations for groups of smaller allies. The UK and Germany have ownership and continue to provide leadership to these initiatives. This is one key reason why they continue to evolve to accommodate changing circumstances and are likely to endure.     

Turkey’s strategic choice: buy or make weapons?

Turkey has been investing in its national defence industrial base since the 1980s. As with other developing countries, Turkey’s motivations for investing in national defence industries can be boiled down to the pursuit of defence autarky, economic benefits and international prestige. However, after 40 years of investment, Turkey is unable to reach the primary goals of defence industrialisation. We argue that three factors are important to understanding Turkey’s persistence in these primary goals. First, Turkey believes that there is an overall improvement in its defence industrial capabilities and the goal of autarky is still reachable. Second, increased defence exports support the belief that Turkish defence industries have become sustainable and the trend will continue in the future. The third reason, perhaps most important of all, has to do with the domestic political gains of defence industrialisation: the AKP uses defence industry and indigenous weapon systems for prestige and, therefore, garners broader support.     

Interactive multicriteria linear programming: An extension of the method of Zionts and Wallenius

This article presents an extension of the interactive multicriteria linear-programming method of Zionts and Wallenius [see Management Science, 29 (5) (1983)]. The decision maker's underlying utility function is assumed to be pseudoconcave, and his preference structure is assessed through pairwise comparison questions. In the method of Zionts and Wallenius, the decision maker's preference structure is represented as constraints on the weights on the objectives derived from his responses. This representation is only a linear approximation to the underlying nonlinear utility function. Accordingly, inconsistency among the constraints on the weights arises while solving the problem. Therefore, some of the constraints have to be dropped, resulting in a loss of information on the preference structure, and hence an increase in the total number of questions. In this article we develop a hybrid representation scheme to avoid this problem. The proposed scheme is implemented within the algorithmic framework of the method of Zionts and Wallenius, and its underlying theory is developed. Computational results show that the number of questions required by the Zionts and Wallenius method can be sinificantly reduced using the proposed scheme.     

Scheduling maintenance and semiresumable jobs on a single machine

The majority of scheduling literature assumes that the machines are available at all times. In this paper, we study single machine scheduling problems where the machine maintenance must be performed within certain intervals and hence the machine is not available during the maintenance periods. We also assume that if a job is not processed to completion before the machine is stopped for maintenance, an additional setup is necessary when the processing is resumed. Our purpose is to schedule the maintenance and jobs to minimize some performance measures. The objective functions that we consider are minimizing the total weighted job completion times and minimizing the maximum lateness. In both cases, maintenance must be performed within a fixed period T, and the time for the maintenance is a decision variable. In this paper, we study two scenarios concerning the planning horizon. First, we show that, when the planning horizon is long in relation to T, the problem with either objective function is NP-complete, and we present pseudopolynomial time dynamic programming algorithms for both objective functions. In the second scenario, the planning horizon is short in relation to T. However, part of the period T may have elapsed before we schedule any jobs in this planning horizon, and the remaining time before the maintenance is shorter than the current planning horizon. Hence we must schedule one maintenance in this planning horizon. We show that the problem of minimizing the total weighted completion times in this scenario is NP-complete, while the shortest processing time (SPT) rule and the earliest due date (EDD) rule are optimal for the total completion time problem and the maximum lateness problem respectively. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 845–863, 1999     

A comparative study of three tool replacement/operation sequencing strategies in a flexible manufacturing system

This paper studies three tool replacement/operation sequencing strategies for a flexible manufacturing system over a finite time horizon: (1) failure replacement—replace the tool only upon failure, (2) optimal preventive tool replacement for a fixed sequence of operations, and (3) joint scheduling of the optimal preventive tool replacement times and the optimal sequence of operations. Stochastic dynamic decision models are used for strategies 2 and 3. The optimization criterion for strategies 2 and 3 is the minimization of the total expected cost over the finite time horizon. We will show through numerical studies that, with the same amount of information, the total expected costs can be reduced considerably by choosing an optimal strategy. Our conclusion is that in flexible manufacturing, optimal tool replacement and optimal operations sequencing are not separate issues. They should be considered jointly to minimize the expected total cost. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 479–499, 2000