Strategic capacity decision‐making in a stochastic manufacturing environment using real‐time approximate dynamic programming

In this study, we illustrate a real‐time approximate dynamic programming (RTADP) method for solving multistage capacity decision problems in a stochastic manufacturing environment, by using an exemplary three‐stage manufacturing system with recycle. The system is a moderate size queuing network, which experiences stochastic variations in demand and product yield. The dynamic capacity decision problem is formulated as a Markov decision process (MDP). The proposed RTADP method starts with a set of heuristics and learns a superior quality solution by interacting with the stochastic system via simulation. The curse‐of‐dimensionality associated with DP methods is alleviated by the adoption of several notions including “evolving set of relevant states,” for which the value function table is built and updated, “adaptive action set” for keeping track of attractive action candidates, and “nonparametric k nearest neighbor averager” for value function approximation. The performance of the learned solution is evaluated against (1) an “ideal” solution derived using a mixed integer programming (MIP) formulation, which assumes full knowledge of future realized values of the stochastic variables (2) a myopic heuristic solution, and (3) a sample path based rolling horizon MIP solution. The policy learned through the RTADP method turned out to be superior to polices of 2 and 3. © 2010 Wiley Periodicals, Inc. Naval Research Logistics 2010     

Lot streaming with supplier–manufacturer coordination

Lot splitting refers to breaking a production lot into smaller sublots during production. Coordinating lot splitting decisions across multiple stages of a production process is a challenging task. Traditional lot splitting and lot streaming models implicitly assume that the entire system is operated and owned by the same firm, or there exists a coordinator who controls the operation of all machines in the system. In this paper, we consider the situation where the machines in a multiple‐stage production process are owned and managed by different companies. Every item in a given production lot has to go through the processing by the supplier's machine, followed by the manufacturer's machine, and so on. We develop and analyze coordination mechanisms that enable different parties in the supply chain to coordinate their lot splitting decisions so as to achieve a systemwide optimum. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

Double Mover–Stayer model on customer switching in telecommunications industry

Customer acquisition and customer retention are the most important challenges in the increasingly competitive telecommunications industry. Traditional studies of customer switching always assume that customers are homogeneous, and thus that model customer switching behavior follows a Markov formulation. However, this postulation is obviously inappropriate in most instances. Blumen et al. (Cornell Studies of Industrial and Labor Relations, Cornell University Press, Ithaca, NY, 1955) developed the Mover–Stayer (MS) model, a generalization of the Markov chain model, to relax the requirement of homogeneity and allow the presence of heterogeneity with two different types of individuals—“stayers,” who purchase the same kinds of products or services throughout the entire observation period; and “movers,” who look for variety in products or services over time. There are two purpose of this article. First, we extend the MS model to a Double Mover‐Stayer (DMS) model by assuming the existence of three types of individuals in the market: (1) stable and loyal customers, who have stable usage within the same company; (2) instable but loyal customers, whose usage varies within the same company over time; and (3) disloyal customers, who switch from one company to another to seek for new experiences or/and benefits. We also propose an estimation method for the DMS model. Second, we apply the DMS model to telecommunications data and demonstrate how it can be used for pattern identification, hidden knowledge discovery, and decision making. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

Multiple subset sum with inclusive assignment set restrictions

In a traditional multiple subset sum problem (MSSP), there is a given set of items and a given set of bins (or knapsacks) with identical capacities. The objective is to select a subset of the items and pack them into the bins such that the total weight of the selected items is maximized. However, in many applications of the MSSP, the bins have assignment restrictions. In this article, we study the subset sum problem with inclusive assignment set restrictions, in which the assignment set of one item (i.e., the set of bins that the item may be assigned to) must be either a subset or a superset of the assignment set of another item. We develop an efficient 0.6492‐approximation algorithm and test its effectiveness via computational experiments. We also develop a polynomial time approximation scheme for this problem. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

Optimal control of a capacitated inventory system with multiple demand classes

This article studies the optimal control of a periodic‐review make‐to‐stock system with limited production capacity and multiple demand classes. In this system, a single product is produced to fulfill several classes of demands. The manager has to make the production and inventory allocation decisions. His objective is to minimize the expected total discounted cost. The production decision is made at the beginning of each period and determines the amount of products to be produced. The inventory allocation decision is made after receiving the random demands and determines the amount of demands to be satisfied. A modified base stock policy is shown to be optimal for production, and a multi‐level rationing policy is shown to be optimal for inventory allocation. Then a heuristic algorithm is proposed to approximate the optimal policy. The numerical studies show that the heuristic algorithm is very effective. © 2011 Wiley Periodicals, Inc. Naval Research Logistics 58: 43–58, 2011     

A new reformulation approach for the generalized partial covering problem

In this paper, we consider a situation in which a group of facilities must be constructed in order to serve a given set of customers, where the facilities might not be able to guarantee an absolute coverage to the different customers. We examine the problem of maximizing the total service reliability of the system subject to a budgetary constraint. We propose a new reformulation of this problem that facilitates the generation of tight lower and upper bounds. These bounding mechanisms are embedded within the framework of a branch‐and‐bound procedure. Computational results on problem instances ranging in size up to 100 facilities and 200 customers reveal the efficacy of the proposed exact and heuristic approaches. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

Combustion characteristic and aging behavior of bimetal thermite powders

Nanothermites have been employed as fuel additives in energetic formulations due to their higher en-ergy density over CHNO energetics. Nevertheless, sintering and degradation of nanoparticles signifi-cantly limit the practical use of nanothermites. In this work, combustion characteristic and aging behavior of aluminum/iron oxide (Al/Fe2O3) nanothermite mixtures were investigated in the presence of micron-scale nickel aimed to produce bimetal thermite powders. The results showed that the alumina content in the combustion residue increased from 88.3％ for Al/Fe2O3 nanothermite to 96.5％ for the nanothermite mixture containing 20 wt％nickel. Finer particle sizes of combustion residue were obtained for the nanothermite mixtures containing nickel, indicative of the reduced agglomeration. Both results suggested a more complete combustion in the bimetal thermite powders. Aging behavior of the nano-thermite mixture was also assessed by measuring the heat of combustion of the mixture before and after aging process. The reduction in heat of combustion of nanothermite mixtures containing nickel was less severe as compared to a significant decrease for the nanothermite mixture without nickel, indicating better aging resistance of the bimetal thermite powders.     

Legitimacy and the Politics of Recognition in Kosovo

Abstract

How do contemporary secessionist movements gain international recognition of their claims to self-determination? I argue that international recognition is forthcoming when a sufficient number of states believe a claim to self-determination ought to be accepted. That is, states recognize claims to self-determination when they perceive them to be legitimate. To convince outsiders of the legitimacy of their claims, separatist movements invoke resonant norms and symbols in a moral economy that structures decision-making. I contrast this argument with prevailing explanations of recognition dynamics. To illustrate the argument, I examine the diplomacy surrounding Kosovo’s independence bid and unilateral secession.     

Programming the procurement of airlift and sealift forces: A linear programming model for analysis of the least-cost mix of strategic deployment systems

A linear programming model for analyzing the strategic deployment mix of airlift and sealift forces and prepositioning to accomplish the composite requirements of a set of possible contingencies is described in this paper. It solves for the least-cost mix of deployment means capable of meeting any one of a spectrum of contingencies, or meeting simultaneous contingencies. The model was developed by RAC as part of the U.S. Army's study program and has been used in analyses of deployment systems conducted in support of the U.S. Army, the Joint Chiefs of Staff and the Office of the Secretary of Defense. Results of analyses have influenced the preparation of long-range plans as well as the formulation of the FY67 Department of Defense budget. The paper gives the background and assumptions of the model, describes the model by means of a simple hypothetical example followed by a selected subset of a complete version, and discusses how the model is used.     

Scheduling jobs and maintenance activities on parallel machines

Most machine scheduling models assume that the machines are available all of the time. However, in most realistic situations, machines need to be maintained and hence may become unavailable during certain periods. In this paper, we study the problem of processing a set of n jobs on m parallel machines where each machine must be maintained once during the planning horizon. Our objective is to schedule jobs and maintenance activities so that the total weighted completion time of jobs is minimized. Two cases are studied in this paper. In the first case, there are sufficient resources so that different machines can be maintained simultaneously if necessary. In the second case, only one machine can be maintained at any given time. In this paper, we first show that, even when all jobs have the same weight, both cases of the problem are NP-hard. We then propose branch and bound algorithms based on the column generation approach for solving both cases of the problem. Our algorithms are capable of optimally solving medium sized problems within a reasonable computational time. We note that the general problem where at most j machines, 1 ≤ j ≤ m, can be maintained simultaneously, can be solved similarly by the column generation approach proposed in this paper. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 145–165, 2000