Changing times: Migrants’ social network analysis and the challenges of longitudinal research

Focusing on migrant social networks, this paper draws upon the sociology of time to incorporate complex notions of temporality into the research process. In so doing, we consider firstly, the challenge of going ‘beyond the snapshot’ in data collection to capture dynamism through time. Secondly, we apply the concepts of timescapes to explore ways of addressing the wider context and the interplay between spatiality, temporality and relationality in migration research. We argue that integrating a mixed methods approach to SNA, crucially including visualisation, can provide a useful methodological and analytical framework to understand dynamics.SNA can also be helpful in bridging the personal and structural dimensions in migration research, by providing a meso level of analysis. However, it is also important to connect the investigation of local and transnational networks with an analysis of the broader social, economic and political contexts in which these take shape; in other words, connecting the micro and the meso with the wider macro level. Drawing upon reflections from our migration research studies, we argue that different combinations of quantitative, qualitative and visual methods do not just provide richer sets of data and insights, but can allow us to better connect conceptualisations – and ontologies – of social networks with specific methodological frameworks.     

Causal inferences on the effectiveness of complex social programs: Navigating assumptions,sources of complexity and evaluation design challenges

This paper explores avenues for navigating evaluation design challenges posed by complex social programs (CSPs) and their environments when conducting studies that call for generalizable, causal inferences on the intervention’s effectiveness. A definition is provided of a CSP drawing on examples from different fields, and an evaluation case is analyzed in depth to derive seven (7) major sources of complexity that typify CSPs, threatening assumptions of textbook-recommended experimental designs for performing impact evaluations. Theoretically-supported, alternative methodological strategies are discussed to navigate assumptions and counter the design challenges posed by the complex configurations and ecology of CSPs. Specific recommendations include: sequential refinement of the evaluation design through systems thinking, systems-informed logic modeling; and use of extended term, mixed methods (ETMM) approaches with exploratory and confirmatory phases of the evaluation. In the proposed approach, logic models are refined through direct induction and interactions with stakeholders. To better guide assumption evaluation, question-framing, and selection of appropriate methodological strategies, a multiphase evaluation design is recommended.     

An integrated approach for water resources decision making under interactive and compound uncertainties

In recent years, the issue of water allocation among competing users has been of great concern for many countries due to increasing water demand from population growth and economic development. In water management systems, the inherent uncertainties and their potential interactions pose a significant challenge for water managers to identify optimal water-allocation schemes in a complex and uncertain environment. This paper thus proposes a methodology that incorporates optimization techniques and statistical experimental designs within a general framework to address the issues of uncertainty and risk as well as their correlations in a systematic manner. A water resources management problem is used to demonstrate the applicability of the proposed methodology. The results indicate that interval solutions can be generated for the objective function and decision variables, and a number of decision alternatives can be obtained under different policy scenarios. The solutions with different risk levels of constraint violation can help quantify the relationship between the economic objective and the system risk, which is meaningful for supporting risk management. The experimental data obtained from the Taguchi's orthogonal array design are useful for identifying the significant factors affecting the means of total net benefits. Then the findings from the mixed-level factorial experiment can help reveal the latent interactions between those significant factors at different levels and their effects on the modeling response.     

A Lower Bound for the Wrap-around L2-discrepancy on Combined Designs of Mixed Two- and Three-level Factorials

The objective of this article is to study the issue of employing the uniformity criterion measured by wrap-around L₂-discrepancy to assess the optimal foldover plans. For mixed two- and three-level fractional factorials as the original designs, general foldover plan and combined design under a foldover plan are defined, and the equivalence between any foldover plan and its complementary foldover plan is investigated. A lower bound of wrap-around L₂-discrepancy of combined designs under a general foldover plan is obtained, which can be used as a benchmark for searching optimal foldover plans. Moreover, it also provides a theoretical justification for optimal foldover plans in terms of uniformity criterion.     

Extension of the pool-adjacent-violators algorithm

The pool-adjacent-violators algorithm (PAVA) is an efficient algorithm which converges in a finite number of steps. However, it has been applicable so far only in isotonic regression with the simple order. This report extends its applicability to other quadratic programming problems, including certain one-sided multivariate testing problems and concave regression problems.     

Selective Maintenance in System Reliability with Random Costs of Repairing and Replacing the Components

In this paper we consider the problem of determining the optimum number of repairable and replaceable components to maximize a system's reliability when both, the cost of repairing the components and the cost of replacement of components by new ones, are random. We formulate it as a problem of non-linear stochastic programming. The solution is obtained through Chance Constrained programming. We also consider the problem of finding the optimal maintenance cost for a given reliability requirement of the system. The solution is then obtained by using Modified E-model. A numerical example is solved for both the formulations.     

Use of concurrent mixed methods combining concept mapping and focus groups to adapt a health equity tool in Canada

The aim of this project was to identify and prioritize a set of conditions to be considered for incorporating a health equity tool into public health practice. Concept mapping and focus groups were implemented as complementary methods to investigate the conditions of use of a health equity tool by public health organizations in Quebec. Using a hybrid integrated research design is a richer way to address the complexity of questions emerging from intervention and planning settings. This approach provides a deeper, operational, and contextualized understanding of research results involving different professional and organizational cultures, and thereby supports the decision-making process. Concept mapping served to identify and prioritize in a limited timeframe the conditions to be considered for incorporation into a health equity tool into public health practices. Focus groups then provided a more refined understanding of the barriers, issues, and facilitating factors surrounding the tools adoption, helped distinguish among participants’ perspectives based on functional roles and organizational contexts, and clarified some apparently contradictory results from the concept map. The combined use of these two techniques brought the strengths of each approach to bear, thereby overcoming some of the respective limitations of concept mapping and focus groups. This design is appropriate for investigating targets with multiple levels of complexity.     

A hybrid genetic algorithm/mathematical programming approach to the multi-family flowshop scheduling problem with lot streaming

This paper presents a hybrid genetic algorithm/mathematical programming heuristic for the n-job, m-machine flowshop problems with lot streaming. The number of sublots for each job and the size of sublots are directly addressed by the heuristic and setups may be sequence-dependent. A new aspect of the problem, the interleaving of sublots from different jobs in the processing sequence, is developed and addressed. Computational results from 12 randomly generated test sets of 24 problems each are presented.     

Duality of the improved algebraic method (DIAM)

In this note we present a variant of the improved algebraic method (IAM) using a duality analysis to solve linear programming (LP) problems where more insights to the method are presented. When the coordinates of all vertices are computed, any feasible point can be expressed as a linear combination of the vertices. The objective function is expressed as a weighted sum of its evaluation at the feasible vertices and the optimal point is associated with the highest/lowest coefficient of the weighted sum.