Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End

In this work, we have attempted to solve two problems concerning the planning and scheduling of crude oil operations: first, on the upstream production planning of crude oil from offshore sources and second, on the scheduling of downstream processing of crude oil at the refinery front-end. The first part is on the offshore oilfield infrastructures planning under both exogenous uncertainty and endogeneous decision-dependent uncertainty. A model representative of the oilfield that is able to select the best routes to obtain the desired objective function is considered. The methodology used is by firstly developing a deterministic model and modeling it with GAMS, followed by a stochastic one. The results obtained show a high accuracy representation in which the uncertainties in both the exogenous and endogeneous uncertainties in planning are accounted for. The stochastic model is a more thorough representation of the problem because it considers all the uncertainties along with the associated probabilities. Having validated the model formulation and solution obtained, we believe that the model can be a useful basic tool to assist upper-level management in deciding on an optimal plan for crude oil production from an offshore operation. The second part is on the scheduling of crude oil operations at a refinery front-end. A technique for obtaining globally optimal schedules for the flow of crude is developed. A continuous time model based on transfer events is used to represent the scheduling problem and this model is a nonconvex MINLP model which presents multiple local optima. We implement a branch-and-contract algorithm that aims at reducing the size of the search region. In order to obtain a global optimum solution of the problem, an outer-approximation algorithm is proposed, whereby lower and upper bounds on the global optimum are generated, which are converged to a specified tolerance. The solution obtained from the LB–MILP model, i.e., the decision variables (binary variables), was used to obtain a feasible solution for model UB–NLP. This solution is the upper bound solution. The application of the proposed algorithm shows significant reduction in the computational effort involved in solving the problem. Slack variables are introduced to overcome the integer infeasibility problem. The optimization model is developed using GAMS and an optimal solution is found with no logical constraints conflicts or error. The main contribution on this work in the first part is to conduct an extensive study on the implementation of the model formulation in Iyer et al. (1998). As well, in the second part, we are focused on investigating effective implementation strategies of the model formulation and solution strategy in Karuppiah et al. (2008) using our choice of the modeling platform GAMS and the best numerical solvers that are available. Hence, most of the exposition on the model formulation and solution algorithms are taken directly from the original papers so as to provide the readers with the most accurate information possible

The impact of Group Intelligence software on enquiry-based learning

Despite the increasing use of groupware technologies in education, there is little evidence of their impact, especially within an enquiry-based learning (EBL) context. In this paper, we examine the use of a commercial standard Group Intelligence software called GroupSystems®ThinkTank. To date, ThinkTank has been adopted mainly in the USA and supports teams in generating ideas, categorising, prioritising, voting and multi-criteria decision-making and automatically generates a report at the end of each session. The software was used by students carrying out an EBL project, set by employers, for a full academic year. The criteria for assessing the impact of ThinkTank on student learning were those of creativity, participation, productivity, engagement and understanding. Data was collected throughout the year using a combination of interviews and questionnaires, and written feedback from employers. The overall findings show an increase in levels of productivity and creativity, evidence of a deeper understanding of their work but some variation in attitudes towards participation in the early stages of the project

EAST-WEST CULTURAL DIFFERENCES IN VISUAL ATTENTION TASKS: IDENTIFYING MULTIPLE MECHANISMS AND DEVELOPING A PREDICTIVE MODEL

Past research has identified East-West differences in visual attention associated with holistic versus analytic perception and reasoning strategies (Nisbett et al., 2001; Boduroglu et al., 2009). These cross-cultural differences might stem from several different mechanisms, which may include: interference suppression, response inhibition, attention to detail vs. object configuration, stimulus centrality vs. eccentricity, number of visual distractors (e.g., display set size or clutter), and others. Although research has shown East-West differences, the results sometimes appear inconsistent with each other, or they lack clear predictions from underlying theories. For example, evidence of a preference for cluttered displays (Wang et al., 2012), evidence for being vulnerable to peripheral distractors (Masuda et al., 2008a), as well as evidence for greater sensitivity to distraction by global information (McKone et al., 2010) are all taken as evidence for the same cultural difference, even if they may be inconsistent with one another (i.e., Easterners prefer displays that are likely to lead to more distraction). This dissertation is comprised of three related efforts: (1) two empirical research studies using multiple visual attentional tasks intended to identify East-West cultural differences in visual attention, (2) identification of the five cultural mechanisms, which are derived from previous cross-cultural studies on general philosophy, visual attention, and bilingualism, aimed at constructing a basis for hypotheses testing, and (3) a computational predictive modeling effort attempting to produce best classification and derive minimal predictors using machine learning schema, along with cross-validating empirical task results. Results reveal inconsistent support for many possible explanations of East-West differences (including bilingual effects, general attentional differences, visual centrality vs. eccentricity) with one explanation finding support in several tasks (detail vs. object configuration). This conclusion is most strongly supported by a global-local interference task (Navon, 1977; McKone et al., 2010) in both experiments conducted, indicating that Easterners were better able to ignore the object information and attend to the contextual detail than Westerners. This conclusion was also supported by results from the dot flicker task and the predictive model. The overall findings suggest that, instead of focusing on high-level descriptive accounts of cultural difference, future research should attempt to investigate how specific attention mechanisms and strategies may differ across cultures

Strongly Regular Graphs Constructed from pp-ary Bent Functions

In this paper, we generalize the construction of strongly regular graphs in [Y. Tan et al., Strongly regular graphs associated with ternary bent functions, J. Combin.Theory Ser. A (2010), 117, 668-682] from ternary bent functions to $p$-ary bent functions, where $p$ is an odd prime. We obtain strongly regular graphs with three types of parameters. Using certain non-quadratic $p$-ary bent functions, our constructions can give rise to new strongly regular graphs for small parameters.Comment: to appear in Journal of Algebraic Combinatoric