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The impacts of increased paper recycling on the U.S. pulp and paper sector are investigated, using the North American Pulp And Paper (NAPAP) model. This dynamic spatial equilibrium model forecasts the amount of pulp, paper and paperboard exchanged in a multi-region market, and the corresponding prices. The core of the model is a recursive price-endogenous linear programming system that simulates the behavior of a competitive industry. The model has been used to make forecasts of key variables describing the sector from 1986 to 2012, based on three recycling policy scenarios. Waste reduction policies that succeed in reducing demand for paper would have the greatest impact on the amount of wood used. But the minimum recycled content policies envisaged currently would have no more effect than what will come about due to unregulated market forces. [ABSTRACT FROM AUTHOR]

In the present paper we generalise the classical newsvendor problem for critical perishable commodities having more severe costs than its linear alternative. Piece wise polynomial cost functions are introduced to accommodate the excess severity. Stochastic demand is assumed to follow a completely unknown probability distribution. Non parametric estimator of the optimal order quantity has been developed from an estimating equation using a random sample. Strong consistency of the estimator is proved for unique optimal order quantity and the result is extended for multiple solutions. Simulation results indicate that non parametric estimator is efficient in terms of mean square error. Real life application of the proposed non-parametric estimator has been demonstrated with Avocado demand in the United States of America and Covid-19 test kit demand during second wave of SARS-COV2 pandemic across 86 countries. [ABSTRACT FROM AUTHOR]

In 2006, the Massachusetts legislature passed a landmark health care reform bill (the Reform) that has served as a model for the national health care reform. By aiming to provide 'access to affordable, quality, accountable health care,' the goals of this reform were to reduce the number of uninsured Massachusetts residents while containing the growth of health care costs and improving the quality of health care services. The current paper examines the impact of the Reform on the quality of care in addition to hospital costs simultaneously from a perspective of efficiency analysis. We develop an integer-valued non-radial Russell data envelopment analysis (DEA) model, which is unit variant and calculate the hospitals' efficiency directly. However, the proposed integer-valued model is non-linear. The current paper thus transforms this model into a parametric integer linear programming. We develop a method to derive its optimal solutions. We then use the new DEA model to calculate and compare the efficiency scores of hospitals in Massachusetts and Connecticut pre- and post-Reform. The analysis shows that the Reform has achieved its cost containment and quality improvement goals at the same time. These analyses provide potentially useful information to hospital regulators and government regulators, especially in light of the national interest on health care legislation. [ABSTRACT FROM AUTHOR]

The earliest documented analytical approach to portfolio selection is Markowitz’s mean-variance analysis, which attempts to find the portfolio with optimal performance by considering the tradeoff between return and risk. The performance of mean-variance analysis has been the subject of many studies and compared to other portfolio construction approaches such as a naïve equally-weighted allocation scheme. In recent years, several approaches have been proposed to improve the mean-variance model by reducing the sensitivity of the portfolio selection process in order achieve robust performance. Although robust portfolio optimization has been one of the most researched methods for improving portfolio robustness, the performance of robust portfolios has not been the major focus of studies. In this paper, a comprehensive analysis on robust portfolio performance is presented for equity portfolios constructed in the U.S. market during the period 1980 and 2014, and results confirm the advantage of robust portfolio optimization for controlling uncertainty while efficiently allocating investments. [ABSTRACT FROM AUTHOR]

Despite powerful advances in interest rate curve modeling for data-rich countries in the last 30 years, comparatively little attention has been paid to the key practical problem of estimation of the term structure of interest rates for emerging markets. This may be partly due to limited data availability. However, emerging bond markets are becoming increasingly important and liquid. It is, therefore, important to be understand whether conclusions drawn from developed countries carry over to emerging markets. We estimate model parameters of fully flexible Nelson-Siegel-Svensson term structures model which has become one of the most popular term structure model among academics, practitioners, and central bankers. We investigate four sets of bond data: U.S. Treasuries, and three major emerging market government bond data-sets (Brazil, Mexico and Turkey). By including both the very dense U.S. data and the comparatively sparse emerging market data, we ensure that are results are not specific to a particular data-set. We find that gradient and direct search methods perform poorly in estimating term structures of interest rates, while global optimization methods, particularly the hybrid particle swarm optimization introduced in this paper, do well. Our results are consistent across four countries, both in- and out-of-sample, and for perturbations in prices and starting values. For academics and practitioners interested in optimization methods, this study provides clear evidence of the practical importance of choice of optimization method and validates a method that works well for the NSS model. [ABSTRACT FROM AUTHOR]

Electricity generation currently is the main industrial source of air emissions in the United States. Both researchers and practitioners are interested in conducting studies to evaluate the ecological performance of this industry, in order to propose solutions to curb emissions of air pollutants and to improve the efficiency of converting fossil resources into electric energy. In this paper, data envelopment analysis (DEA) is used to assess ecological efficiency where air emissions are used as undesirable outputs. Although conventional DEA does not require a priori information on the input and output weights, weight restrictions can be incorporated to reflect a user's preference over the performance metrics, or to refine the DEA results. Adding weight restrictions voids the fact that DEA scores are independent of the units of measurement. To incorporate weight constraints in ecological efficiency assessment, this paper develops a DEA model that is units-invariant when weight restrictions are imposed. Moreover, the proposed model is equivalent to the standard units-invariant DEA model when weight restrictions are not present. [ABSTRACT FROM AUTHOR]

This paper studies the dynamic interactions of the ethanol, crude oil and corn market prices in the United States from January 2005 up to December 2014. The empirical analysis, for the shake of robustness, employs alternative time series methodologies based on single equation and system estimation approaches to cointegration and more specifically, the autoregressive distributed lags and the Johansen ML cointegration methodologies were applied complementary. The findings reveal a statistically significant long-run causal effect running from crude oil and corn prices to ethanol price as well as from ethanol and corn prices to crude oil price. Additionally, a positive relationship between crude oil price and ethanol price was revealed. [ABSTRACT FROM AUTHOR]

Lean as a business strategy is used to improve quality and service, eliminate waste, reduce time and costs, and enhance overall organizational effectiveness. Heightening challenges in competition in recent years have prompted many small and medium-sized enterprises (SMEs) to adopt lean to enhance firms' competitiveness. This paper attempts to present an all-inclusive study and it examines various factors associated with the implementation of lean in SMEs in the U.S. The findings suggest that most of SMEs have a relatively accurate understanding of lean concept and philosophy. The primary reasons to implement lean are mainly internal, including reduce cost, improve profit margin, improve utilization of plant/facility, and maintain competitive position. A hierarchical cluster analysis was conducted to investigate lean status. It was discovered that both advanced adopters and beginners of lean are discovered. ANOVA test results show that there exist quite significant differences in terms of the degrees of lean implementation in SMEs. Varied lean tools and programs have been applied and they are positively related with firms' performance. Lastly, the paper provides evidences that major lean barriers are encountered by SMEs regarding management or people related factors as well as key knowledge and know-how. [ABSTRACT FROM AUTHOR]

There are essentially two alternatives to analyse the impacts of tax reform proposals on risk-taking: the two-asset model and the certainty equivalent approach. Here risk-taking is defined in terms of the certainty equivalent approach. The paper discusses the effects of current tax reform proposals in the Federal Republic of Germany and in the United States with respect to risk-taking. Among others it is shown that there are unambiguous effects of the reform proposals as far as the upper income class is considered. Furthermore, the paper studies some impacts of the transition from the FRG-schedule T88 (coming into force at the beginning of 1988) to an intended schedule characterized by a linearly increasing marginal tax rate. [ABSTRACT FROM AUTHOR]

The increasing vulnerability of the population from frequent disasters requires quick and effective responses to provide the required relief through effective humanitarian supply chain distribution networks. We develop scenario-robust optimization models for stocking multiple disaster relief items at strategic facility locations for disaster response. Our models improve the robustness of solutions by easing the difficult, and usually impossible, task of providing exact probability distributions for uncertain parameters in a stochastic programming model. Our models allow decision makers to specify uncertainty parameters (i.e., point and probability estimates) based on their degrees of knowledge, using distribution-free uncertainty sets in the form of ranges. The applicability of our generalized approach is illustrated via a case study of hurricane preparedness in the Southeastern United States. In addition, we conduct simulation studies to show the effectiveness of our approach when conditions deviate from the model assumptions. [ABSTRACT FROM AUTHOR]

We investigate how in the context of Corporate Venture Capital (CVC), the investment decisions affect the likelihood of their subsequent exit strategies. We use OLS and probit regression as well as Weibull distribution of residual values, given its reliability and validity for studying lifetime analysis. Based on a sample of 8722 VC-backed ventures with the first investment dates between 1999 and 2018 in United States (US) and United Kingdom (UK), the results show that the presence of CVCs positively affects the funding amounts and the duration of the investment. CVC funds are more generous and more patient than Independent Venture Capital (IVC) funds regarding their investments in ventures. Moreover, the findings provide evidence that the exit strategies are directly influenced by the funding amounts and the duration of the investment which are influenced, in turn, by the fund type. Greater funding increases the likelihood of IPO exit which is reduced by longer investment duration. Our results are robust to alternative estimation methods, namely two-stage treatment-effects regressions. These results help the various stakeholders (VC funds, investors, ventures) make crucial decisions regarding investment amounts and duration, and exit. [ABSTRACT FROM AUTHOR]

Previous research has established a need for operations research models to help urban public housing authorities (PHAs) in the U.S. better manage the transition from the traditional model of high-rise public housing developments to tenant-based housing subsidies for market-rate rental units and project-based housing subsidies for scattered-site, low-density public housing. This paper presents the tenant-based subsidized housing location model (TSHLP) that is simplified and applied to a larger and more representative data set than has been done previously. Base-case and sensitivity analyses indicate that model solutions, which are approximations to a Pareto frontier of nondominated potential family allocations, give planners considerable flexibility in choosing alternative housing configurations that can satisfy the needs of various interest groups. [ABSTRACT FROM AUTHOR]

The electricity industry is undergoing a substantial process of restructuring, with an emphasis on the introduction of competition in the generation sector. Traditional planning methods are not necessarily appropriate for this new environment. This paper extends a previously developed linear programming model to the problem of optimal expansion planning in the face of uncertainty. The model explicitly accounts for equipment availability and load duration curves in selecting optimal investment. The use of the model is illustrated with a simple 2-region problem calibrated with data from Hydro-Québec and the northeastern United States that suggests how the LP model can help decision makers. [ABSTRACT FROM AUTHOR]

This paper presents a two-stage multi-period decision model for allocation of the individual's savings into several investment plans. Although the U.S. economy is used as the background, the modelling methods are general enough to accommodate any tax law. The first stage of the model uses an asset-allocation method based on the single-index model. Because this method is static and does not provide for tax considerations and other constraints, it alone is not enough. The output of this optimal selection is used as exogenous parameters and controls for the second stage of the model which is an integer program. The IP includes fixed charges, statutory and budgetary constraints, a discount rate, and the risk level. We provide an example of this approach to illustrate how an individual can achieve his goals of terminal accumulations while maintaining the risk level, measured by the aggregate beta, he prefers. A linear programming relaxation of the IP model is utilized for sensitivity analysis to examine whether future adjustments in investment strategies are required. The model remains tractable enough for implementation by individuals who may not be experts in mathematical programming and financial planning. [ABSTRACT FROM AUTHOR]

This paper investigates the financial-economic decision process for investments in flexible manufacturing systems (FMS). Contrary to popular belief, we show that conventional capital budgeting techniques can be used to make such investment decisions. First, we identify the overall impact of installing an FMS and present guidelines for a cash flow forecasting model. We then present ways in which to incorporate uncertainty in these cash flows within a risk-adjusted discount rate. These expected cash flows and the discount rate are used in calculating the net present value (NPV). Once the capital budgeting analysis is completed, a critical issue facing the firm is the optimal timing of the installation. We reinterpret the general results on optimal timing of investments within the special context of an FMS project. Finally, we illustrate the above technique via a stylized example. [ABSTRACT FROM AUTHOR]

The design and use of flexible manufacturing systems (FMSs) involve some intricate operations research problems. FMS design problems include, for example, determining the appropriate number of machine tools of each type, the capacity of the material handling system, and the size of buffers. FMS planning problems include the determination of which parts should be simultaneously machined, the optimal partition of machine tools into groups, allocations of pallets and fixtures to part types, and the assignment of operations and associated cutting tools among the limited-capacity tool magazines of the machine tools. FMS scheduling problems include determining the optimal input sequence of parts and an optimal sequence at each machine tool given the current part mix. FMS control problems are those concerned with, for example, monitoring the system to be sure that requirements and due dates are being met and that unreliability problems are taken care of. This paper defines and describes these FMS problems in detail for OR/MS researchers to work on. [ABSTRACT FROM AUTHOR]

The Mineral Resources Institute of the Colorado School of Mines is completing a project sponsored jointly by the Gas Research Institute and the Electric Power Research Institute to assess the cost of development of natural gas resources in the United States. The project has as its objective the development of a method and subsequent calculation* of costs which might be anticipated in the discovery and development of the undiscovered natural gas resources of the nation. Costs are expressed in constant dollars and are intended to provide a measure of the relative costs which would be encountered in various regions and at various depths. The project work was supported by the development of a model for calculation of full marginal costs of resource discovery and development by Operational Economics, Inc. This paper summarizes the data sources, methodology, and results of the analyses performed, as well as some interpretations of those results. Additionally, the paper includes some possible applications of the procedures and the models to the estimation of the costs of development of the oil resources of the United States and of the oil and gas resources of the world. [ABSTRACT FROM AUTHOR]

A topic of recent interest in the retail financial sector has been the growth of credit unions or 'pure cooperatives'. Past credit union researchers built mathematical models of credit union operations. These models identified important operating characteristics but were modeled under assumptions of static operating environments. The model presented in this paper departs from the traditional static models and examines dynamic operation for a United States credit union. Its inter-temporal structure clarifies a number of issues-such as optimal equity retention and inter-temporal rate policy-not addressed by earlier studies. Given initial conditions, the model specifies equity retention and inter-temporal deposit and loan rate policies until an equilibrium state is reached. [ABSTRACT FROM AUTHOR]

In this paper, we investigate how many containers would need to be screened in order to deter attackers from attempting to smuggle weapons into a defending country in container freight. We hypothesize that with a sufficiently high probability of being detected, attackers might be deterred from smuggling attempts. Thus, our goal is to identify the optimal proportion of containers to inspect in order to minimize the defender's expected loss, using game theory to reflect the fact that attackers are simultaneously trying to maximize their expected rewards. Moreover, our model recognizes that the container-screening policy must simultaneously protect against different types of threats (such as nuclear bombs, dirty bombs, and assault rifles). Finally, our model also suggests that threatening to retaliate against attacks may be beneficial to defenders, as long as the threat is credible. [ABSTRACT FROM AUTHOR]

In this paper, a decision support tool that automates crew recovery during irregular operations for large-scale commercial airlines is presented. The tool is designed for airlines that adopt the hub-spoke network stru cture. The advance of this tool over the existing ones is that it recovers projected crew problems that arise due to current system disruptions. In other words, it proactively recovers crew problems ahead of time before their occurrence. In addition, it gives a wide flexibility to react to different operation scenarios. Also, it solves for the most efficient crew recovery plan with the least deviation from the originally planned schedule. The tool adopts a rolling approach in which a sequence of optimization assignment problems is solved such that it recovers flights in chronological order of their departure times. In each assignment problem, the objective is to recover as many flights as possible while minimizing total system cost resulting from resource reassignments and flight delays. The output of this tool is in the form of new crew trippairs that cover flights in the considered horizon. A test case is presented to illustrate the model capabilities to solve a real-life problem for one of the major commercial airlines in the U.S. [ABSTRACT FROM AUTHOR]

In general in an organisation whose system of governance involves weighted voting, a member's weight in terms of the number of votes and the formal power it represents differ. Power indices provide a means of analysing this difference. The paper uses new algorithms for computing power indices for large games. Three analyses are carried out: (1) the distribution of Banzhaf voting power among members in 1999: the results show that the United States has considerably more power over ordinary decisions than its weight of 17% but that the use of special supermajorities limits its power: (2) the effect of varying the majority requirement on the power of the IMF to act and the powers of members to prevent and initiate action (Coleman indices); the results show the effect of supermajorities severely limits the power to act and therefore renders the voting system ineffective in democratic terms, also the sovereignty of the United States within the IMF is effectively limited to just the power of veto: (3) the paper proposes the determination of the weights instrumentally by means of an iterative algorithm to give the required power distribution: this would be a useful procedure for determining appropriate changes in weights consequent on changes to individual countries' quotas; this is applied to the 1999 data. Policy recommendations are, first, that the IMF use only simple majority voting, and discontinue using special supermajorities, and, second, allocate voting weight instrumentally using power indices. [ABSTRACT FROM AUTHOR]

Evaluating the practice patterns of the newly dominant force in managed care, the primary care gatekeeper, will be one of the toughest challenges facing health reformers in the United States. This paper introduces DEA as a tool to profile and evaluate practice patterns of primary care physicians. To illustrate these ideas, the practice behavior of 326 primary care physicians in a large Health Maintenance Organization were studied for one year. When two DEA models were compared, a cone ratio DEA model projected the excess utilization of more hospital days and fewer office visits than a DEA model without defined preferred practice regions. The application demonstrates how a cone ratio DEA model can incorporate strategic thinking and executive accountability when establishing clinical benchmarks. [ABSTRACT FROM AUTHOR]

The Pacific Gas and Electric Company, the largest investor-owned energy utility in the United States, obtains a significant fraction of its electric energy and capacity from hydrogeneration. Although hydro provides valuable flexibility, it is subject to usage limits and must be carefully scheduled. In addition, the amount of energy available from hydro varies widely from year to year, depending on precipitation and streamflows. Optimal scheduling of hydrogeneration, in coordination with other energy sources, is a stochastic problem of practical significance to PG&E. SOCRATES is a system for the optimal scheduling of PG&E's various energy sources over a one- to two-year horizon. This paper concentrates on the component of SOCRATES that schedules hydro. The core is a stochastic optimization model, solved using Benders decomposition. Additional components are streamflow forecasting models and a database containing hydrological information. The stochastic hydro scheduling module of SOCRATES is undergoing testing in the user's environment, and we expect PG&E hydrologists and hydro schedulers to place progressively more reliance upon it. [ABSTRACT FROM AUTHOR]

Unless procedures for the economic evaluation of flexible manufacturing technology axe revamped, much of U.S. industry could repeat the experience of American automobile and steel companies from the recent past. The dynamic character of flexible manufacturing technology in terms of associated developments in microelectronics, a trend toward equipment modularity, and the increasing diversity of relevant markets make flexible manufacturing especially vulnerable to the weaknesses of conventional procedures for the justification of capital expenditures. Building on the work of V. Smith, M.I. Kamien and N.L. Schwartz, this paper presents optimization models from which economically, reasonable plans can be derived for the implementation of flexible manufacturing technology. Although the assumptions of these models are not focused on the situation of a specific plant, model implications and the overall perspectives here on the economic evaluation of flexible system options should provide general guidance for manufacturing planners. [ABSTRACT FROM AUTHOR]

In this paper we develop a novel formulation for the empty railcar distribution problem that considers realistic technical and business requirements while assigning empty cars to customer demands. The proposed model takes block and train capacities into account, while satisfying the supply and demand constraints, and allows car substitutability among pools of the same car type as well as customer preferences towards different pools. Following the practice in US railroads, the proposed model does not combine car routing and car distribution decisions. Those two decisions are separated from each other and they are usually made by different departments in US railroads. The model is implemented in CPLEX Concert Technology using Java and is illustrated in a numerical example. Results show that the proposed model can improve several performance measures over the noncapacitated model which is currently used by industry. [ABSTRACT FROM AUTHOR]

We build a model under the framework of discrete optimization to explain how high frequency trading (HFT) can be applied to supply liquidity and reduce execution cost. We derive the analytical properties of our model in finding the optimal solution to minimize the overall execution cost of HFT. We show that the execution cost can be reduced after increasing trading frequency (i.e., the higher the trading frequency, the lower the execution cost) with a simulation study. In addition, we conduct an empirical investigation with tick level data from US equity market through January 2008 to October 2010 to verify our conclusion drawn from the simulation study. Based on the simulation and empirical results we collected, we show that the HFT can reduce the execution cost when supplying liquidity. [ABSTRACT FROM AUTHOR]

Together with regular retail channel, a firm can distribute products directly through Internet (referred to as an 'e-tail' distribution channel). The competitive edge of the retail channel lies in more value-added services, some of which are unavailable through the e-tail channel. We consider a model mixed with retailing and e-tailing distribution channels where the service level and price decision are made, respectively, ex ante and ex post demand realizations. From the firm's perspective of managing the two channels, we acquire the optimal decisions and characterize the effects of the demand uncertainty on the firm's optimal retail service and expected profit. Applying stochastic comparison method, we show the firm's retail service and profit both increase in the demand mean, and the firm profits from the increase of the convex order of the demand by decreasing his service level. Further, if the coefficient of the demand increases, we characterize that the firm benefits from it. Finally, several numerical studies are presented to gain insights. [ABSTRACT FROM AUTHOR]

One way countries like the United States can comply with suggested rollbacks in greenhouse gas emissions is by employing power plants fueled with biomass. We examine the competitiveness of biomass-based fuel for electrical power as opposed to coal using a mathematical programming structure. We consider fueling power plants from milling residues, whole trees, logging residues, switch grass, or short-rotation woody crops. We do this using a combined model of the agricultural and forestry sectors. We find that the competitiveness of biomass depends in a key way upon the success of research in developing improved production methods for short-rotation woody crops without great increases in costs. [ABSTRACT FROM AUTHOR]

Data envelopment analysis (DEA) is a broadly used non-parametric technique for performance evaluation and data analytics. While conventional single-stage DEA models overlook the internal interactions of decision making units (DMUs), network DEA opens this black box to investigate the internal structure of DMUs. Practically, many network DEA models involve shared performance measures that are not easily divisible among individual components of a network. Based upon a two-stage network DEA model, the current study treats such performance measures as inseparable links, implying that no proportions are optimized and allocated to the two stages of the network. The shared and unsplittable links in the proposed two-stage DEA model manifest integrality while both ends of the link are maximized or minimized simultaneously, and this setting has not been modeled in any existing DEA studies. The shared and unsplittable links in our model can be considered intermediate measures, but they are different from the two existing types of dual-role intermediate measures, which are traditional intermediate measures and feedback measures. Our performance link is a new type of intermediate measure that is minimized or maximized in both stages of the network. The resulting network DEA model is highly non-linear. To address the non-linearity, a parametric linear model is adopted. The proposed approach is construed in four variants, and then illustrated using a set of 100 banks in the United States. [ABSTRACT FROM AUTHOR]

When publishing tabular data, the United States Bureau of the Census must sometimes round fractional data to integer values or round integer data to multiples of a prespecified base. Data integrity can be maintained by rounding tabular data subject to additivity constraints while minimizing the overall perturbation of the data. In this paper, we describe a heuristic based on tabu search with strategic oscillation for solving this NP-hard problem. A lower-bounding technique is developed in order to evaluate the quality of the solutions and provide a starting solution for the tabu search. Numerical results demonstrate the effectiveness of the procedure when applied to extremely large tables with up to 27,000 randomly generated entries. Additionally, the algorithm is shown to perform extremely well when applied to actual data obtained from the United States Bureau of the Census. [ABSTRACT FROM AUTHOR]

Mitigating the disastrous effects of natural disasters by performing preparation activities is one of the main purposes of relief organizations. However, the high degree of uncertainty associated with disasters impedes the work of aid agencies considerably. In this regard, two-stage stochastic programs are often used in the relevant literature to support decision making in these situations. An accelerated L-shaped method is proposed in this work, which solves realistic large-scale two-stage stochastic problems within a reasonable time-frame, allowing relief organizations to react to short-term forecasts, as e.g. available in case of hurricanes or floods. In particular, computation times needed for solving the resulting sub-problems via a specialized interior-point method are significantly reduced by exploiting the specific structure of second-stage constraints. To show the superiority of this approach with respect to solution times, a realistic large-scale case study is developed for America's hurricane-prone south-east coast. The accelerated L-shaped method outperforms the standard L-shaped method significantly whereas a commercial solver failed to solve the case study within an acceptable time-frame. [ABSTRACT FROM AUTHOR]

Regulatory reform enacted (e.g., the Dodd-Frank Act enforced in the U.S.) requires the financial service industry to consider the "reasonably expected near term demand" (i.e., RENTD) in trading. To manage the price impact and transaction cost associated with orders submitted to an order driven market, market makers or specialists must determine their trading styles (aggressive, neutral, or passive) based on the market liquidity in response to RENTD, particularly for trading a large quantity of some financial instrument. In this article we introduce a model considering different trading styles to satisfy the predictive near-term customer demand of market liquidity in order to find an optimal order submission strategy based on different market situations. We show some analytical properties and numerical performances of our model in search of optimal solutions. We evaluate the performances of our model with simulations run over a set of experiments in comparison with two alternative strategies. Our results suggest that the proposed model illustrates superiority in performance. [ABSTRACT FROM AUTHOR]

This study addresses stock selection modeling and portfolio construction and implementation in global and U.S. markets in the context of multi-objectives optimization framework. We will show how forecasted earnings acceleration factors can enhance returns in global and U.S. stock markets. We construct Markowitz portfolios for Global and U.S. domestic Markets that offer superior returns-to-risk ratios, relative to domestic portfolios. We show how stock repurchases and corporate exports can be estimated and implemented as the third objective to generate statistically significant excess returns in global and U.S. stock markets. It is particularly interesting to note the conflicting corporate strategies’ impacts on stockholder wealth. [ABSTRACT FROM AUTHOR]

In general, the demand rate moving through a product life cycle can be reasonably depicted by a trapezoidal-type pattern: it initially increases during the introduction and growth phases, then remains reasonably constant in the maturity phase, and finally decreases in the decline phase. It is evident that perishable products deteriorate continuously over time and can not be sold after its maximum lifetime. Thus, the deterioration rate of a product is increasing with time and closely related to its maximum lifetime. Furthermore, it has been hard to obtain loans from banks since the global financial meltdown in 2008. Hence, over 80% of firms in the United Kingdom and the United States sell their products on various short-term, interest-free loans (i.e., trade credit) to customers. To incorporate those important facts, we develop an inventory model by (1) assuming the demand pattern is trapezoidal, (2) extending the deterioration rate to 100% as its maximum lifetime is approaching, (3) using discounted cash-flow analysis to calculate all relevant costs considering the effects of upstream and downstream trade credits, and (4) including the costly purchase cost into the total cost, which is omitted in previous studies. Then, the order quantity that maximizes the present value of the profit is uniquely determined. Finally, through numerical examples, managerial insights are provided. [ABSTRACT FROM AUTHOR]

Identifying the optimal screening strategies for breast cancer, the second leading cause of female cancer deaths in the US, is a major societal problem creating much controversy. The optimal screening strategies significantly depend on the sensitivity and specificity of the screening modality used. While the current state-of-the-art screening technology is mammography, its sensitivity or specificity may increase over time, or mammography may be replaced by another technology such as tomosynthesis in the near future. The purpose of this study is to identify the optimal use of the next generation of breast cancer screening modalities, whose sensitivity and specificity in clinical practice are either yet unknown or keep improving over time. Contrary to the prior literature that focuses on finding the optimal screening policy for given sensitivity and specificity values, we take an inverse optimization approach and focus on finding the range of sensitivity and specificity values, for which a given screening policy is optimal. To replicate breast cancer progression in the US population under various screening policies, we develop a parametric Partially Observable Markov Chain (POMC) model, which accounts for unobservable and age-specific disease progression, age-specific mortality, and the possibility of detecting cancer without a screening exam (either via self-detection or a clinical breast exam). We then formulate a nonlinear program (NLP) to identify the range of sensitivity and specificity values that optimize a particular screening policy. We show that this NLP is nonconvex for some parameter values, and hence difficult to solve. We prove several structural properties of the model, and by exploiting these properties, we propose a complete solution algorithm for this problem. We use real data in our numerical analysis and show that with the current technology, biennial breast cancer screening is slightly better than annual screening for the average-risk population. We also find that an improvement only in sensitivity (but not in specificity) will not change the current optimal policy. Furthermore, we characterize the lost potential quality-adjusted life years (QALYs) due to suboptimal practice, and show that biennial screening is more robust than annual screening in the sense that it results in fewer lost QALYs due to choosing a suboptimal screening policy. Given that the design of multicenter clinical trials may be prohibitively expensive and lengthy, our findings may be especially valuable to policymakers in deciding about the optimal use of an emerging breast cancer screening modality, and adapting a new technology in different settings. [ABSTRACT FROM AUTHOR]

We describe our design and implementation of a dual-objective course-timetabling system for the Science Division at Rollins College, and we compare the results of our system with the actual timetable that was manually constructed for the Fall 2009 school term. The course timetables at Rollins, as at most colleges in the U.S., must be created before students enroll in classes, and our 'wish list' of pairs of classes that we would like to offer in non-overlapping timeslots is considerably larger than if we were to consider only those that absolutely must be in non-overlapping timeslots. This necessitates assigning different levels of conflict severity for the class pairs and setting our objective to minimize total conflict severity. Our second objective is to create timetables that result in relatively compact schedules for the instructors and students. In addition to our automatic construction, a second, equally important component of our system is a graphical user interface (GUI) that enables the user to participate in the input, construction, and modification of a timetable. In the input phase, course incompatibility, instructor and student preferences, and desire for compact schedules all require subjective judgments. The GUI allows the user to quantify and convert this information to the weighted-graph model. In the construction and modification phase, the GUI enables the user to directly assign or reassign courses to timeslots while guided by heuristics. [ABSTRACT FROM AUTHOR]

We study a supply chain scheduling problem, where a common due date is assigned to all jobs and the number of jobs in delivery batches is constrained by the batch size. Our goal is to minimize the sum of the weighted number of tardy jobs, the due-date-assignment costs and the batch-delivery costs. We show that some well-known $\mathcal{NP}$-hard problems reduce to our problem. Then we propose a pseudo-polynomial algorithm for the problem, establishing that it is $\mathcal{NP}$-hard only in the ordinary sense. Finally, we convert the algorithm into an efficient fully polynomial time approximation scheme. [ABSTRACT FROM AUTHOR]

The fast growing U.S. mobile wireless industry has been experiencing dramatic technological change and substantial competition. As a result of these catalysts, we argue that wireless firms have experienced significant productivity improvement and provide new evidence that technological progress almost exclusively contributed to productivity improvements in the wireless industry by significantly expanding the production possibilities set. We employ nonparametric estimation procedures based on Data Envelopment Analysis (DEA) that utilize input-output data from a representative sample of 16 firms in the mobile wireless industry to estimate productivity change, technological change, and relative efficiency change for the period spanning the years from 2000 to 2002. Our findings show that the industry experienced a significant growth of 13% in productivity, which was primarily due to an average technological progress of 9.9% in the industry. Additionally, we find that national wireless operators experienced significantly higher productivity growth and contributed more to technological progress than regional providers. Firms that were industry pioneers as evidenced by high market share at the beginning of our sample period experienced higher productivity growth and greater technological progress compared to firms with lower initial market share. Moreover, the industry experienced significantly higher productivity growth and technical progress in the later sample period between 2001 and 2002 than in the early period between 2000 and 2001. [ABSTRACT FROM AUTHOR]

This article offers background information on the monograph "Normative Analysis in Policy Decisions," an outgrowth of an American Association for Advancement of Science (AAAS) Symposium, Normative Analysis, at the 1983 AAAS Annual Meeting in Detroit, Michigan. The papers emphasize interdisciplinary applications and operational methods which have enhanced factual understanding of real economic systems.

A DEA framework is used to examine changes in administrative employment in U.S. manufacturing industries between 1983 and 1989, using data collected by the U.S. Department of Labor. Among other findings, the analysis suggests that production technology is important factor in explaining inter-industry differences in administrative staffing. In addition, ‘best practice’ staffing efficiencies for Batch industries are shown to hold a distinct (and statistically significant) advantage over that for Line industries. On related issues, this research uncovers no evidence of the ‘dramatic decreases’ in overhead staffing were suggested in the popular business press during this time period. Clear structural differences in administrative staffing intensities, however, are noted with respect to manufacturing production technology. In their usage of overhead staff, Batch industries tend to more ‘professional-worker’ intensive, while Line industries are relatively more ‘nonprofessional- worker’ intensive. These patterns hold up over time and are statistically confirmed in an analysis of DEA ‘cones’. [ABSTRACT FROM AUTHOR]

A GPSS/H model is presented for a hypothetical flexible manufacturing system. The FMS consists of six machines composed of three machine types, manufactures three types of parts, and uses automatic guided vehicles (AGVs) to transport in-process parts between appropriate machines and wait spaces in the system. Three logical modules have been designed for the model, with copies of these modules then being appropriately distributed and interfaced throughout the model and tailored to achieve overall representation of the specific FMS. The same technique can be used by others to build analogous or extended GPSS/H models for other specific FMSs in which AGVs are used as transporters. Simulations can then be performed with such models to research FMS design and control alternatives. [ABSTRACT FROM AUTHOR]

Inclusion of the shadow prices for natural gas in a dynamic fuels model for the United States shows that the primary reason for the relatively large fly-up in new marginal gas prices in the early 1980's was the release of the pent-up price effects of the U.S. government's price regulations. In accordance with principles, the shadow price of natural gas fell siginificantly following de-regulation of the high-cost gas (section 107) in 1980, which represented the precursor for downward adjustments in marginal wellhead prices of new high-cost gas and drilling activity. The modeling results show that no significant fly-up in new marginal gas prices for lower-cost gas (section 102) is likely to occur in 1985, when its phased de-regulation ends and it is finally de-regulated, because no shadow price precursor currently exists for this gas. Shadow price principles clear up the primary misconceptions with regard to natural gas pricing. This application indicates the significance of shadow price principles for regulated pricing in general. [ABSTRACT FROM AUTHOR]

Focuses on the life and works of professor Abraham Charnes in the U.S. Dedication to the truth, to knowledge and to science; Reverence to great teachers, great thinkers and researchers; Loyalty in his relationship at work and in his private life.