RAISING THE COST OF REBELLION: THE ROLE OF THIRD‐PARTY INTERVENTION IN INTRASTATE CONFLICT

This paper presents a simple model to characterize explicitly the role that an intervening third party plays in raising the cost of rebellion in an intrastate conflict. Extending the Gershenson‐Grossman (2000 Gershenson, D. and Grossman, H.I. 2000. Civil conflict: ended or never ending?. Journal of Conflict Resolution, 44(6): 807–821.  [Google Scholar]) framework of conflict in a two‐stage game to the case involving outside intervention in a three‐stage game as in Chang et al. (2007b Chang, Y.‐M., Potter, J. and Sanders, S. 2007b. War and peace: third‐party intervention in conflict. European Journal of Political Economy, 23(4): 954–974.  [Google Scholar]), we examine the conditions under which an outside party optimally intervenes such that (i) the strength of the rebel group is diminished or (ii) the rebellion is deterred altogether. We also find conditions in which a third party optimally intervenes but at a level insufficient to deter rebellion. Such behavior, which improves the incumbent government’s potential to succeed in conflict, is overlooked in some conflict studies evaluating the effectiveness of intervention. One policy implication of the model is that an increase in the strength of inter‐governmental trade partnerships increases the likelihood that third‐party intervention deters rebellion.     

MILITARY EXPENDITURE AND UNEMPLOYMENT RATES: GRANGER CAUSALITY TESTS USING GLOBAL PANEL DATA

This paper investigates the empirical relationships between military expenditure and unemployment rates. A set of global panel data on 46 countries is utilized, and a panel data version of the Granger causality test is applied. The results indicate that there is little evidence of the causality running from unemployment to military expenditure regardless of how we measure military spending and determine group countries. In contrast, the causality running from military expenditure to unemployment receives empirical support if military expenditure is measured in terms of its share of GDP and if data are taken from middle‐ and low‐income countries or non‐OECD countries.     

A mathematical formulation and efficient heuristics for the dynamic container relocation problem

The container relocation problem (CRP) is concerned with emptying a single yard‐bay which contains J containers each following a given pickup order so as to minimize the total number of relocations made during their retrieval process. The CRP can be modeled as a binary integer programming (IP) problem and is known to be NP‐hard. In this work, we focus on an extension of the CRP to the case where containers are both received and retrieved from a single yard‐bay, and call it the dynamic container relocation problem. The arrival (departure) sequences of containers to (from) the yard‐bay is assumed to be known a priori. A binary IP formulation is presented for the problem. Then, we propose three types of heuristic methods: index based heuristics, heuristics using the binary IP formulation, and a beam search heuristic. Computational experiments are performed on an extensive set of randomly generated test instances. Our results show that beam search heuristic is very efficient and performs better than the other heuristic methods.Copyright © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 101–118, 2014     

Optimizing usage and maintenance decisions for k‐out‐of‐n systems of moving assets

We consider an integrated usage and maintenance optimization problem for a k‐out‐of‐n system pertaining to a moving asset. The k‐out‐of‐n systems are commonly utilized in practice to increase availability, where n denotes the total number of parallel and identical units and k the number of units required to be active for a functional system. Moving assets such as aircraft, ships, and submarines are subject to different operating modes. Operating modes can dictate not only the number of system units that are needed to be active, but also where the moving asset physically is, and under which environmental conditions it operates. We use the intrinsic age concept to model the degradation process. The intrinsic age is analogous to an intrinsic clock which ticks on a different pace in different operating modes. In our problem setting, the number of active units, degradation rates of active and standby units, maintenance costs, and type of economic dependencies are functions of operating modes. In each operating mode, the decision maker should decide on the set of units to activate (usage decision) and the set of units to maintain (maintenance decision). Since the degradation rate differs for active and standby units, the units to be maintained depend on the units that have been activated, and vice versa. In order to minimize maintenance costs, usage and maintenance decisions should be jointly optimized. We formulate this problem as a Markov decision process and provide some structural properties of the optimal policy. Moreover, we assess the performance of usage policies that are commonly implemented for maritime systems. We show that the cost increase resulting from these policies is up to 27% for realistic settings. Our numerical experiments demonstrate the cases in which joint usage and maintenance optimization is more valuable. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 418–434, 2017     

Bayesian sampling plans for exponential distributions with interval censored samples

This article studies the problem of designing Bayesian sampling plans (BSP) with interval censored samples. First, an algorithm for deriving the conventional BSP is proposed. The BSP is shown to possess some monotonicity. Based on the BSP and using the property of monotonicity, a new sampling plan modified by the curtailment procedure is proposed. The resulting curtailed Bayesian sampling plan (CBSP) can reduce the duration time of life test experiment, and it is optimal in the sense that its associated Bayes risk is smaller than the Bayes risk of the BSP if the cost of the duration time of life test experiment is considered. A numerical example to compute the Bayes risks of BSP and CBSP and related quantities is given. Also, a Monte Carlo simulation study is performed to illustrate the performance of the CBSP compared with the BSP. The simulation results demonstrate that our proposed CBSP has better performance because it has smaller risk. The CBSP is recommended. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 604–616, 2015     

Dynamic inventory control with limited capital and short‐term financing

For most firms, especially the small‐ and medium‐sized ones, the operational decisions are affected by their internal capital and ability to obtain external capital. However, the majority of the literature on dynamic inventory control ignores the firm's financial status and financing issues. An important question that arises is: what are the optimal inventory and financing policies for firms with limited internal capital and limited access to external capital? In this article, we study a dynamic inventory control problem where a capital‐constrained firm periodically purchases a product from a supplier and sells it to a market with random demands. In each period, the firm can use its own capital and/or borrow a short‐term loan to purchase the product, with the interest rate being nondecreasing in the loan size. The objective is to maximize the firm's expected terminal wealth at the end of the planning horizon. We show that the optimal inventory policy in each period is an equity‐level‐dependent base‐stock policy, where the equity level is the sum of the firm's capital level and the value of its on‐hand inventory evaluated at the purchasing cost; and the structure of the optimal policy can be characterized by four intervals of the equity level. Our results shed light on the dynamic inventory control for firms with limited capital and short‐term financing capabilities.Copyright © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 184–201, 2014     

Strategic obfuscation of production capacities

Recent supply‐chain models that study competition among capacity‐constrained producers omit the possibility of producers strategically setting wholesale prices to create uncertainty with regards to (i.e., to obfuscate) their production capacities. To shed some light on this possibility, we study strategic obfuscation in a supply‐chain model comprised of two competing producers and a retailer, where one of the producers faces a privately‐known capacity constraint. We show that capacity obfuscation can strictly increase the obfuscating producer's profit, therefore, presenting a clear incentive for such practices. Moreover, we identify conditions under which both producers' profits increase. In effect, obfuscation enables producers to tacitly collude and charge higher wholesale prices by moderating competition between producers. The retailer, in contrast, suffers a loss in profit, raises retail prices, while overall channel profits decrease. We show that the extent of capacity obfuscation is limited by its cost and by a strategic retailer's incentive to facilitate a deterrence. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 244–267, 2014     

Exact algorithms for integrated facility location and production planning problems

We consider a class of facility location problems with a time dimension, which requires assigning every customer to a supply facility in each of a finite number of periods. Each facility must meet all assigned customer demand in every period at a minimum cost via its production and inventory decisions. We provide exact branch‐and‐price algorithms for this class of problems and several important variants. The corresponding pricing problem takes the form of an interesting class of production planning and order selection problems. This problem class requires selecting a set of orders that maximizes profit, defined as the revenue from selected orders minus production‐planning‐related costs incurred in fulfilling the selected orders. We provide polynomial‐time dynamic programming algorithms for this class of pricing problems, as well as for generalizations thereof. Computational testing indicates the advantage of our branch‐and‐price algorithm over various approaches that use commercial software packages. These tests also highlight the significant cost savings possible from integrating location with production and inventory decisions and demonstrate that the problem is rather insensitive to forecast errors associated with the demand streams. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

Monitoring the market or the salesperson? The value of information in a multilayer supply chain

We study a supply chain in which a manufacturer relies on a salesperson to sell the products to the consumers. The sales outcome is determined by a random market condition and the salesperson's service level, both of which are privately observed by the salesperson. Apart from them, there are two types of resellers: a knowledgeable reseller observes the market condition, whereas a diligent reseller can monitor the service level. While delegating to a reseller enhances information acquisition, it may also result in double marginalization and inefficiency. We identify several operating regimes in which double marginalization can be eliminated via simple contracts and establish the benefit of monitoring the salesperson over monitoring the market. Our dominance result is not prone to our model characteristics regarding the complementarity of market condition and sales effort, the relative importance of adverse selection and moral hazard, and the contract form. We then generalize our model and re‐establish the dominance result in the presence of reseller's risk aversion or private monitoring expertise. We also quantify the performance gaps among different selling schemes under various scenarios. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011