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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]

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]

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]

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]

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]

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]

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]

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]

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]