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AbstractThe National Football League (NFL) in the United States expanded to 32 teams in 2002 with the addition of a team in Houston. At that point, the league was realigned into eight divisions, each containing four teams. We describe a branch‐and‐cut algorithm for minimizing the sum of intradivisional travel distances. We consider first the case where any team can be assigned to any division. We also consider imposing restrictions, such as aligning the AFC (American Football Conference) and the NFC (National Football Conference) separately or maintaining traditional rivalries. We show that the alignment chosen by the NFL does not minimize the sum of intradivisional travel distances, but that it is close to optimal for an alignment that aligns the NFC and AFC separately and imposes some additional restrictions. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 683–701, 2003.

AbstractThis article formulates and solves a stochastic optimization model to investigate the impact of crowdsourced platforms (e.g., ridesharing, on‐demand delivery, volunteer food rescue, and carpooling) offering small, personalized menus of requests and incentive offers for drivers to choose from. To circumvent nonlinear variable relationships, we exploit model structure to formulate the program as a stochastic linear integer program. The proposed solution approach models stochastic responses as a sample of variable and fixed scenarios, and to counterbalance solution overfitting, uses a participation ratio parameter. The problem is also decomposed and iterated among two separate subproblems, one which optimizes menus, and another, which optimizes incentives. Computational experiments, based on a ride sharing application using occasional drivers demonstrate the importance of using multiple scenarios to capture stochastic driver behavior. Our method provides robust performance even when discrepancies between predicted and observed driver behaviors exist. Computational results show that offering menus and personalized incentives can significantly increase match rates and platform profit compared to recommending a single request to each driver. Further, compared to the menu‐only model, the average driver income is increased, and more customer requests are matched. By strategically using personalized incentives to prioritize promising matches and to increase drivers' willingness to accept requests, our approach benefits both drivers and customers. Higher incentives are offered when drivers are more likely to accept, while fewer incentives and menu slots are reserved for driver‐request pairs less likely to be accepted.

PurposeThe purpose of this study is to present an assessment of the sustainability content of the Nigerian engineering curriculum in universities.Design/methodology/approachContent analysis is used to generate and analyse data from three engineering documents, namely, the Benchmark Minimum Academic Standards for Engineering Programmes in Nigeria and the engineering handbooks of two Nigerian higher education institutions.FindingsThe Nigerian engineering curriculum is revealed to have a low sustainability content, with environmental concepts being the most cited themes and social topics as the least stated issues.Research limitations/implicationsThe sustainability assessment approach adopted in the study is constrained by the question of what constitutes a sustainability syllabus. Expert-derived sustainability themes used in the study are unavoidably incomplete and may limit the conduct of an exhaustive sustainability content assessment.Practical implicationsBased on the research outcome, the Council for the Regulation of Engineering in Nigeria and other stakeholders can consider ways to adequately incorporate sustainability themes in the Nigerian engineering curriculum.Originality/valueThe research is an effort to determine the presence of sustainability issues in the Nigerian engineering education, which has hitherto been scarcely documented. This study provides a baseline and a rationale for sustainability education interventions in the Nigerian engineering curriculum. It also presents a methodology for analysing sustainability content in university curriculum and contributes to the continuing sustainability education discourse, especially in relation to sub-Saharan Africa.

We develop a methodology for evaluating a decision strategy
generated by a stochastic optimization model. The methodology is
based on a pilot study in which we estimate the distribution of
performance associated with the strategy, and define an appropriate
stratified sampling plan. An algorithm we call filtered search
allows us to implement this plan efficiently. We demonstrate the
approach's advantages with a problem in asset / liability management
for an insurance company.