A Stochastic Goal Program for Employee Scheduling*

Deterministic goal programs for employee scheduling decisions attempt to minimize expected operating costs by assigning the ideal number of employees to each feasible schedule. For each period in the planning horizon, managers must first determine the amount of labor that should be scheduled for duty. These requirements are often established with marginal analysis techniques, which use estimates for incremental labor costs and shortage expenses. Typically, each period in the planning horizon is evaluated as an independent epoch. An implicit assumption is that individual employees can be assigned to schedules with as little as a single period of work. If this assumption violates local work rules, the labor requirements parameters for the deterministic goal program may be suboptimal. As we show in this research, this well-known limitation can lead to costly staffing and scheduling errors. We propose an employee scheduling model that overcomes this limitation by integrating the labor requirements and scheduling decisions. Instead of a single, externally determined staffing goal for each period, the model uses a probability distribution for the quantity of labor required. The model is free to choose an appropriate staffing level for each period, eliminating the need for a separate goal-setting procedure. In most cases this results in better, less costly decisions. In addition, the proposed model easily accommodates both linear and nonlinear under- and overstaffing penalties. We use simple examples to demonstrate many of these advantages and to illustrate the key techniques necessary to implement our model. We also assess its performance in a study of more than 1,700 simulated stochastic employee scheduling problems.     

Solution Procedures for the Lot-Streaming Problem

Lot streaming is the process of splitting a job into sublots so its operations can be overlapped and its progress accelerated. We present a computationally efficient procedure for solving the m-machine, two-sublot problem, and we discuss the bottleneck insights that emerge from the analysis. We also examine heuristic approaches for more than two sublots and discuss computational results for these procedures.     

Roads to American Empire: U.S. Military Public Works and Capitalist Transitions, 1898–1934.

Between 1898 and 1934, in synchronous and successive U.S. military interventions and occupations in Cuba, Puerto Rico, the Philippines, Haiti, and the Dominican Republic, American soldiers made public works, and especially roads, into a global technology of imperial power. This essay examines infrastructure as a factor in state formation and capitalist transition in these five different imperial spaces as a way to study U.S. empire, and its effects on foreign societies, through a comparative, global, and intra‐imperial approach often precluded by the methodological nationalism of historical and sociological literatures. Despite significant differences between these sites of U.S. war and occupation, both prior to American interventions and during them, U.S. military public works expressed and advanced a common political‐economic logic of state centralization and capital accumulation. Colonial and post‐colonial political institutions and political economies, the strength of central governments, the extent of plantation agriculture and rural proletarianization, world commodity markets, and geography and natural events varied, but determined U.S. imperial infrastructure's outcomes. By the 1930s, the U.S. military had elevated infrastructural improvement to a key repertoire of American imperial power in the world, and one which persisted as the United States turned away from formal colonialism in the era of the Cold War and decolonization.     

Understanding foraging flexibility in urban vervet monkeys,Chlorocebus pygerythrus,for the benefit of human-wildlife coexistence

Urban Ecosystems - Generalist wildlife species often thrive in urban environments because of increased anthropogenic resources. However, human-wildlife interactions, especially if negative, raise...     

An elastic-net penalized expectile regression with applications

To perform variable selection in expectile regression, we introduce the elastic-net penalty into expectile regression and propose an elastic-net penalized expectile regression (ER-EN) model. We then adopt the semismooth Newton coordinate descent (SNCD) algorithm to solve the proposed ER-EN model in high-dimensional settings. The advantages of ER-EN model are illustrated via extensive Monte Carlo simulations. The numerical results show that the ER-EN model outperforms the elastic-net penalized least squares regression (LSR-EN), the elastic-net penalized Huber regression (HR-EN), the elastic-net penalized quantile regression (QR-EN) and conventional expectile regression (ER) in terms of variable selection and predictive ability, especially for asymmetric distributions. We also apply the ER-EN model to two real-world applications: relative location of CT slices on the axial axis and metabolism of tacrolimus (Tac) drug. Empirical results also demonstrate the superiority of the ER-EN model.     

Quality of Life in Intentional Communities

The present study was initiated to investigate levels and predictors of wellbeing among inhabitants of intentional communities (ICs). An anonymous, Internet-based questionnaire was distributed to US and Canadian ICs. Responses were obtained from 913 members. Wellbeing was measured by the widely used satisfaction with life scale (SWLS). Hierarchical linear regression analyses were run to test the predictive validity of Social support, Identity fusion, Meaning in life, Community satisfaction and Life change, and Religious activity above and beyond demographic variables and personality traits. Mean scores on the SWLS were estimated to 5.27 and 5.47 (1–7 scale) for men and women, respectively. The full model explained 41.4% of the variance for men and 38.2% for women. Personality explained 13.4 (men) and 14.4% (women) of the variation, while demographic variables only had a minor impact. Overall, presence of Meaning in life and Social support were the most important predictors. The IC inhabitants reported wellbeing on par with the highest scores previously published. The findings support the contention that sustainability, in the form of a communal lifestyle of low ecological footprint, may be promoted without forfeiting wellbeing.     

The Times They are A’changing: Multigenerational Family Simulations

Multigenerational households are increasingly affecting both the individual and family as well as community organizations and social policies. Social work and other family studies students can profit from educational modalities that use adult learning applications through a systems life-course perspective, the whole family aging over time. Family simulation software—addressing multigenerational families, such as two or more adult generations living together—builds on a previous paper (Marriage & Family Review, Feb. 2015). Social class, among other demographic and environmental variables, is emphasized. Agent-based family social network simulation of multigenerational families can facilitate experiential learning. An automatically generated life events report, based on both factual data and specific family characteristics, can be used as a classroom case study for role playing and assessing.     

URBAN TRANSPORTATION MODE CHOICE AND TRIP COMPLEXITY: BICYCLISTS STICK TO THEIR GEARS

Commuters' lives have become more complicated with rising income. In my model, transportation mode choices are made simultaneously with the choice of whether to make multiple stops. Using travel behavior data, I estimate the model using an error components logit (ECL) specification to account for commuters' unobserved preferences for particular modes and find that omitting unobserved preferences underestimates value of travel time relative to the crossing‐components ECL. The estimated model predicts that increased trip complexity causes substitution away from public transit to automobiles, with the exception that bicyclists transition only to more complex trips and do not change transportation modes. (JEL R41, C25)