In this paper we propose a multiperiod nonlinear programming model for the production planning
and product distribution of several continuous multiproduct plants that are located in different
sites and supply different markets. The unique feature of the proposed model is that each plant
is represented through nonlinear process models. To solve the resulting large-scale model, we
present two solution techniques based on Lagrangean decomposition. Spatial decomposition is
based on the idea of dualizing interconnection constraints between the plants and markets in
order to be able to optimize each site and market individually. For the temporal decomposition,
the interconnection constraints are defined between each time period through the inventory
variables so that the entire production and distribution plan can be optimized independently in
each time period. It is shown that the proposed decomposition methods yield significant
computational savings, and temporal decomposition is shown to be the superior decomposition
approach in terms of faster computational times and tighter bounds to the optimal solutions.
The retrofit design of a network of processes over several time periods is addressed in this paper. A strategy is proposed that consists of a high level to analyze the entire network and a low level to analyze a specific process flowsheet in detail. A methodology is presented for the high level to model process flowsheets and retrofit modifications using a multiperiod generalized disjunctive programming (GDP) model. This problem is reformulated as a mixed-integer linear program (MILP) using the convex hull formulation. Two examples that illustrate the proposed model are presented. The results show that the proposed GDP model provides a significant benefit over the existing network without retrofit and provides a clear advantage over intuitively choosing modifications based on heuristics. To illustrate the performance benefits of using the convex hull formulation, the problem is also modeled as an MILP with big-M constraints.
Objective: Nutrition backlash is a disposition defined by negative feelings about dietary recommendations. Past research has measured nutrition backlash using the nutrition backlash scale (NBS), and found that it is negatively related to fruit and vegetable consumption. The present study examined several aspects of the NBS, including factor structure, discriminant validity, and relationship to demographics and health behaviors.Research Methods & Procedures: Adults were recruited to participate in two studies. Study 1 (N = 480) included measures of nutritional backlash, information overload, worry, fatalism, and nutrition-related behaviors. Study 2 (N = 399) was a follow-up that examined the factor structure of the NBS in a separate sample.
Results:In Study 1, a six-item version of the NBS was found to be a good fit for the data and discriminant from overload, worry, and fatalism. NBS was higher for those with less education, non-White participants, and males. Individuals with higher backlash were also less likely to look at nutritional labels and to use sunscreen. Study 2 confirmed the factor structure from Study 1.
Conclusions:A six-item version of NBS was found to be reliable, discriminant from related measures, higher in underserved groups (less educated, non-White, and male participants), and related to nutrition label use.
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