An iterated greedy algorithm for the flowshop scheduling problem with blocking

This paper proposes an iterated greedy algorithm for solving the blocking flowshop scheduling problem for makespan minimization. Moreover, it presents an improved NEH-based heuristic, which is used as the initial solution procedure for the iterated greedy algorithm. The effectiveness of both procedures was tested on some of Taillard’s benchmark instances that are considered to be blocking flowshop instances. The experimental evaluation showed the efficiency of the proposed algorithm, in spite of its simple structure, in comparison with a state-of-the-art algorithm. In addition, new best solutions for Taillard’s instances are reported for this problem, which can be used as a basis of comparison in future studies.     

Too Big to Learn: The Effects of Major Acquisition Failures on Subsequent Acquisition Divestment

We examine whether firms learn from their major acquisition failures. Drawing from a threat‐rigidity theoretical framework, we suggest that firms do not learn from their major acquisition failures. Furthermore, we hypothesize that host‐country experience reinforces the negative effects of major acquisition failures. Our research hypotheses are tested using an event history analysis of 741 acquisitions undertaken by French listed and non‐listed firms in the USA between January 1988 and December 2008. We use failure divestment (divestment resulting from acquisition failure) as a proxy for acquisition performance. Consistent with our theoretical framework, we find that major acquisition failures have a negative impact on future acquisition performance. Furthermore, we find that such negative effects are reinforced by firms’ host‐country experience.     

Non-parametric inference for the effect of a treatment on survival times with application in the health and social sciences

In this paper we perform inference on the effect of a treatment on survival times in studies where the treatment assignment is not randomized and the assignment time is not known in advance. Two such studies are discussed: a heart transplant program and a study of Swedish unemployed eligible for employment subsidy. We estimate survival functions on a treated and a control group which are made comparable through matching on observed covariates. The inference is performed by conditioning on waiting time to treatment, that is, time between the entrance in the study and treatment. This can be done only when sufficient data are available. In other cases, averaging over waiting times is a possibility, although the classical interpretation of the estimated survival functions is lost unless hazards are not functions of waiting time. To show unbiasedness and to obtain an estimator of the variance, we build on the potential outcome framework, which was introduced by J. Neyman in the context of randomized experiments, and adapted to observational studies by D.B. Rubin. Our approach does not make parametric or distributional assumptions. In particular, we do not assume proportionality of the hazards compared. Small sample performance of the estimator and a derived test of no treatment effect are studied in a Monte Carlo study.     

Examining Identity Consolidation Processes Among Ethnic Minority Gay Men and Lesbians

Legal recourse is a vital avenue for many domestic violence victims. For lesbian, gay, and bisexual (LGB) people, these laws have historically been heterosexist. Considering the many states that are now inclusive of same-gender relationships, an existing data set was utilized to examine the influence of sociodemographic predictors on the perceptions of domestic violence law among LGB. Our findings illustrate that nonwhite LGB and those who have negative perceptions of law enforcement have the most negative perceptions of domestic violence legal protections as they apply to same-gender relationships. These findings have implications for service providers, advocacy and outreach organizations, and future research exploring the impact perceptions of legal avenues have on LGB victims.     

Impaired Self-Awareness in Pathological Gamblers

Lack of self-awareness of one’s decisions remains an understudied and elusive topic in the addiction literature. The present study aimed at taking a first step towards addressing this difficult subject through the use of a combination of behavioral procedures. Here, we explored the association between a metacognitive process (the ability to reflect and evaluate the awareness of one’s own decision) and poor performance on the Iowa Gambling Task (IGT) in a group of pathological gamblers (PG; n = 30), and in a comparison group (n = 35). This metacognitive process was assessed during the IGT with the post-decision wagering procedure, while a number of potential confounds (i.e., reward/loss sensitivity, dual-tasking) were controlled for. Results showed that: (1) Initial performance enhancement of the control group on IGT occurred without explicit knowledge of the task, thus confirming its implicit character; (2) compared to controls, performance of PG on the IGT failed to increase during the task; (3) taking into account increased reward sensitivity and decreased loss sensitivity as well as poorer dual-tasking in pathological gamblers, PG tended to exhibit a bias in evaluating their own performance on the IGT by maximizing their wagers independently of selecting advantageous decks. Our findings suggest that biased metacognition may affect pathological gamblers, leading to disadvantageous post-decision wagering, which is in turn linked to impaired decision making under ambiguity. Perhaps this deficit reflects the impaired insight and self-awareness that many addicts suffer from, thus providing a novel approach for capturing and measuring this impairment, and for investigating its possible causes.     

Combinatorial design of a minimum cost transfer line

The problem of equipment selection for a production line is considered. Each piece of equipment, also called unit or block, performs a set of operations. All necessary operations of the line and all available blocks with their costs are known. The difficulty is to choose the most appropriate blocks and group them into (work)stations. There are some constraints that restrict the assignment of different blocks to the same station. Two combinatorial approaches for solving this problem are suggested. Both are based on a novel concept of locally feasible stations. The first approach combinatorially enumerates all feasible solutions, and the second reduces the problem to search for a maximum weight clique. A boolean linear program based on a set packing formulation is presented. Computer experiments with benchmark data are described. Their results show that the set packing model is competitive and can be used to solve real-life problems.     

Gender Gaps in Educational Outcomes Among Children of New Migrants: The Role of Social Integration from a Comparative Perspective

This article reviews current research on gender gaps in educational outcomes among children of new migrants (first, 1.5, and second generations) from a comparative cross‐national perspective. The article examines potential explanations for why gendered differences in educational outcomes among immigrants (vis‐à‐vis non‐migrants) continue to occur, focusing on individual, schooling, and institutional factors. For example, while gender gaps in expectations and aspirations as well as some cognitive outcomes are increasing (reading ability is considerably higher among females) and shrinking in specific subjects (e.g. math and science ability is slightly higher among boys), that process often has been less explored within and across immigrant vis‐à‐vis non‐immigrant students. We show that in some countries, gender gaps among disadvantaged ethnic minorities (in relation to other groups) continue to persist and are exacerbated by institutional factors. These disadvantages vary not only across different educational systems and at different rates over time but also are based on students' social background. Overall, we argue that these educational inequalities are key to understanding not only the socioeconomic and future political adaptation of migrants and their children but also future social policy developments in the European Union context.     

Experimentation order with good properties for 2 k factorial designs

Randomizing the order of experimentation in a factorial design does not always achieve the desired effect of neutralizing the influence of unknown factors. In fact, with some very reasonable assumptions, an important proportion of random orders achieve the same degree of protection as that obtained by experimenting in the design matrix standard order. In addition, randomization can induce a large number of changes in factor levels and thus make experimentation expensive and difficult. De Leon et al. [Experimentation order in factorial designs with 8 or 16 runs, J. Appl. Stat. 32 (2005), pp. 297–313] proposed experimentation orders for designs with eight or 16 runs that combine an excellent level of protection against the influence of unknown factors, with the minimum number of changes in factor levels. This article presents a new methodology to obtain experimentation orders with the desired properties for designs with any number of runs.