Deutsche Bahn Schedules Train Rotations Using Hypergraph Optimization

Deutsche Bahn (DB) operates a large fleet of rolling stock (locomotives, wagons, and train sets) that must be combined into trains to perform rolling stock rotations. This train composition is a special characteristic of railway operations that distinguishes rolling stock rotation planning from the vehicle scheduling problems prevalent in other industries. DB models train compositions using hyperarcs. The resulting hypergraph models are addressed using a novel coarse-to-fine method that implements a hierarchical column generation over three levels of detail. This algorithm is the mathematical core of DB's fleet employment optimization (FEO) system for rolling stock rotation planning. FEO's impact within DB's planning departments has been revolutionary. DB has used it to support the company's procurements of its newest high-speed passenger train fleet and its intermodal cargo locomotive fleet for crossborder operations. FEO is the key to successful tendering in regional transport and to construction site management in daily operations. DB's planning departments appreciate FEO's high-quality results, ability to reoptimize (quickly), and ease of use. Both employees and customers benefit from the increased regularity of operations. DB attributes annual savings of 74 million euro, an annual reduction of 34,000 tons of CO2 emissions, and the elimination of 600 coupling operations in crossborder operations to the implementation of FEO

Determinants of successful lifestyle change during a 6-month preconception lifestyle intervention in women with obesity and infertility

Purpose: To identify demographic, (bio)physical, behavioral, and psychological determinants of successful lifestyle change and program completion by performing a secondary analysis of the intervention arm of a randomized-controlled trial, investigating a preconception lifestyle intervention. Methods: The 6-month lifestyle intervention consisted of dietary counseling, physical activity, and behavioral modification, and was aimed at 5–10% weight loss. We operationalized successful lifestyle change as successful weight loss (≥ 5% weight/BMI ≤ 29 kg/m2), weight loss in kilograms, a reduction in energy intake, and an increase in physical activity during the intervention program. We performed logistic and mixed-effect regression analyses to identify baseline factors that were associated with successful change or program completion. Results: Women with higher external eating behavior scores had higher odds of successful weight loss (OR 1.10, 95% CI 1.05–1.16). Women with the previous dietetic support lost 0.94 kg less during the intervention period (95% CI 0.01–1.87 kg). Women with higher self-efficacy reduced energy intake more than women with lower self-efficacy (p < 0.01). Women with an older partner had an increased energy intake (6 kcal/year older, 95% CI 3–13). A high stage of change towards physical activity was associated with a higher number of daily steps (p = 0.03). A high stage of change towards weight loss was associated with completion of the intervention (p = 0.04). Conclusions: Determinants of lifestyle change and program completion were: higher external eating behavior, not having received previous dietetic support, high stage of change. This knowledge can be used to identify women likely to benefit from lifestyle interventions and develop new interventions for women requiring alternative support. Trial registration: The LIFEstyle study was registered at the Dutch trial registry (NTR 1530; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=1530).</p

Determinants of successful lifestyle change during a 6-month preconception lifestyle intervention in women with obesity and infertility

Purpose: To identify demographic, (bio)physical, behavioral, and psychological determinants of successful lifestyle change and program completion by performing a secondary analysis of the intervention arm of a randomized-controlled trial, investigating a preconception lifestyle intervention. Methods: The 6-month lifestyle intervention consisted of dietary counseling, physical activity, and behavioral modification, and was aimed at 5–10% weight loss. We operationalized successful lifestyle change as successful weight loss (≥ 5% weight/BMI ≤ 29 kg/m2), weight loss in kilograms, a reduction in energy intake, and an increase in physical activity during the intervention program. We performed logistic and mixed-effect regression analyses to identify baseline factors that were associated with successful change or program completion. Results: Women with higher external eating behavior scores had higher odds of successful weight loss (OR 1.10, 95% CI 1.05–1.16). Women with the previous dietetic support lost 0.94 kg less during the intervention period (95% CI 0.01–1.87 kg). Women with higher self-efficacy reduced energy intake more than women with lower self-efficacy (p < 0.01). Women with an older partner had an increased energy intake (6 kcal/year older, 95% CI 3–13). A high stage of change towards physical activity was associated with a higher number of daily steps (p = 0.03). A high stage of change towards weight loss was associated with completion of the intervention (p = 0.04). Conclusions: Determinants of lifestyle change and program completion were: higher external eating behavior, not having received previous dietetic support, high stage of change. This knowledge can be used to identify women likely to benefit from lifestyle interventions and develop new interventions for women requiring alternative support. Trial registration: The LIFEstyle study was registered at the Dutch trial registry (NTR 1530; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=1530)