Entropy-based selection with multiple objectives

In this article we present an approach to determine the initially unspecified weights in an additive measurable multiattribute value function. We formulate and solve a series of nonlinear programming problems which (1) incorporate whatever partial information concerning the attribute weights or overall relative value of alternatives the decision maker chooses to provide, yet (2) yield a specific set of weights as a result. Although each formulation is rather easily solved using the nonlinear programming software GINO (general interactive optimizer), solutions in closed form dependent on a single parameter are also provided for a number of these problems.     

Do Employers Favor those with Military Experience in the U.S. Reserve Forces? Evidence from a Field Experiment

This study examines whether completed service in the military reserves results in a civilian labor market benefit. Reservists are not completely absent from the civilian labor market during their military service, possibly allowing them to receive the benefits associated with military experience without forgoing valuable civilian labor market experience. Using a resume study, the results suggest that completed service in the military reserves, relative to no military experience, increases the probability of receiving a request for an interview by 19%.     

Component part stocking policies

This article presents research designed to aid firms who assemble many components into a final product. We assume that purchase quantities are fixed, and that all parts and components are assembled at one stage in a short time. Demand for the final product is represented by a stationary independent and identically distributed random variable; and unmet demand is backordered. Ordering is done on a periodic review basis. We develop infinite horizon, approximate expected cost, and expected service level functions, and we present an algorithm for finding approximately minimum cost reorder points for each part subject to a service level constraint. Extensive results on the accuracy of the approximations are presented. Due to the size of the problem, we present only limited results on the performance of the optimization algorithm.     

An algorithm for the discrete bilevel programming problem

The bilevel programming problem (BLPP) is an example of a two-stage, noncooperative game in which the first player can influence but not control the actions of the second. This article addresses the linear formulation and presents a new algorithm for solving the zero-one case. We begin by converting the leader's objective function into a parameterized constraint, and then attempt to solve the resultant problem. This produces a candidate solution that is used to find a point in the BLPP feasible reagion. Incremental improvements are sought, which ultimately lead to a global optimum. An example is presented to highlight the computations and to demonstrate some basic characteristics of the solution. Computational experience indicates that the algorithm is capable of solving problems with up to 50 variables in a reasonable amount of time.     

See the light: Optimization of put-to-light order picking systems

Put-to-light order picking systems invert the basic logic of conventional picker-to-parts systems. Instead of successively visiting the storage positions of the stock keeping units (SKUs) when collecting picking orders, an order picker accompanies successive bins each containing multiple items of a specific SKU along a lane of subsequent orders. Whenever the picker passes an order requiring the current SKU, which is indicated by a light signal, she puts the requested number of items into the bin associated with the order. Such an order picking system is well-suited if the assortment is not overly large and all orders demand similar SKUs, so that it is mainly applied in distribution centers of brick-and-mortar retail chains. This paper evaluates four different setups of put-to-light systems, which, during operations, require the solution of different storage assignment and SKU sequencing problems. We formulate these problems, prove computational complexity, and suggest suited solution algorithms. By applying these algorithms in a comprehensive computational study, we benchmark the impact of the four different setups on picking performance. In this way, warehouse managers receive decision support on how to set up their put-to-light systems.     

Scheduling prowler training

The U.S. Navy Prowler aircraft is designed for electronic surveillance and countermeasures. In this paper, we describe the problem of scheduling Prowler crew training, and we present two integer programming models to solve it. The first model maximizes the number of aviators trained above 75% in each mission area, subject to the available number of flights, over a single month. The second model distinguishes peacetime from mobilization, and minimizes the number of flights done in mobilization subject to the available number of flights in peacetime. Our models distinguish different types of crew and allow more than one qualification to be earned on a given flight. We give numerical results using real data, comparing our results to the actual readiness of a squadron. We found that crew readiness of Prowler squadrons can be increased by 10%, simply by better scheduling. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 289–305, 2003.     

The demand for defense in East Asia: Modeling security alternatives∗

An interactive economic model of military spending is proposed. It is quantified on the basis of cross section data for East Asia. Projections of military spending to the end of the decade suggest that the growth of military spending in the region will decline slightly in the current decade. East Asian military spending can, however, be greatly influenced by the path of Chinese and US military efforts. An expansion of military spending by China could cause neighboring countries to greatly increase their military expenditures.     

TERRORISM AND DETERRENCE POLICY WITH TRANSNATIONAL SUPPORT 1

This study provides an explanation of terrorism by examining interactions between the terrorist group with a minority as a potential pool of recruits and the government supported by a majority. A hawkish deterrence policy makes it more risky for terrorists to launch attacks, but heightens the anti‐government feeling of the terrorist group. In addition, the payoff for the government depends not only on the payoff loss associated with the level of terrorism, but also on the political payoff from the action itself of adopting a hawk policy due to its politicians’ vested interests. We first show that whether the deterrence policy should be ‘hawk to ‘dove is closely dependent on the relationships among the risk associated with terrorism, the anti‐government feeling of the terrorist group, and the political payoff for the government. This study then introduces transnational support enhancing the capability of a terrorist group to intensify its activity and shows that the emergence of transnational support may cause the government to reform its deterrence policy from ‘dove’ toward ‘hawk,’ with terrorism intensified in the society.