Some of the complex logistical problems faced by companies combine the needs for strategic and tactical decisions concerning the interrelated issues of clustering, scheduling, and routing. Various strategies can be used to solve these problems. We present a problem of this type, involving a company whose fundamental objective is the commercialization of its product in the domestic market. The paper focuses on a model of and method for a solution to the problem of scheduling visits to customers, taking into account the relationship with other phases of product marketing. The model is nonlinear, involves binary and continuous variables, and solved heuristically. Computational experiments show that the proposed solution performed very well for both real-life and theoretical instances.

Introduction: this work proposes a model, and two heuristic algorithms to assign customers to trucks and visiting days, as a first phase in the solution of a real-world routing problem, which is closely related to the Periodic vehicle routing problem, but a strategic decision of the company imposes the additional constraint that every customer must always be visited by the same truck. Methods: The proposed model aims to group the customers that are visited the same day by the same truck as close as possible. The first proposed heuristic has a constructive stage, and five underlying improvement heuristic, the second one uses an exact linear programming algorithm. Results: The algorithms are evaluated by instances taken from the literature and generated, taking into account the characteristics presented in the real-world case addressed.

The formation of software development project teams is carried out, conventionally, in an empiric manner; however, in this process, multiple factors should be considered. In literature, the works where this process is modeled are scarce, and most do not consider aspects linked to the formation of the team as a whole. In this paper, a group of patterns that contribute to the formation of software development projects teams are identified through the use of the Delphi method, psychological tests, and data mining tools. The paper identifies patterns that are validated experimentally, while psychological characteristics in the process of software team formations are exemplified.

While advancements in machine learning are increasing rapidly, very little progress has been made in its mass adoption despite its benefits in assistive technologies for older adults. By examining how users interact with smart technologies, characteristics of trust can be identified and enhanced to increase adoption of the next generation of assistive systems. The current study conducted a literature review to understand better how trust with autonomous systems is formed and maintained. Twenty-two pertinent articles were identified in which three themes emerged. First, people tend to forgive human errors more than errors made by machines -- meaning mistrust is exaggerated when systems make mistakes. Second, the development of trust depends on how the system solves the tasks it is assigned, for instance if a user does not believe the system acted in an “ethical way,” distrust may form and the continuation of adoption is decreased. Lastly, trust depends on the situation and the risk/reward associated with using the system, for example the trust needed to board an autonomous plane differs from that for a simple grammar correction. Taken together, the black box ideology of autonomous systems may be an issue that prevents trust in them to be formed and maintained. Promising future directions are to create machine language translators that improve transparency of autonomous system behaviors (i.e., explainability). Even if assistive technologies are created to aid older adults -- the lack of focus on understanding the factors that foster trust may dampen their actual use.

Stereotype threat is defined as the situational predicament when people feel at risk of conforming to social stereotypes. Correspondingly, stereotype threat may negatively impair a persons’ working memory and cognitive abilities during neuropsychological tests due to hyper awareness of negative stereotypes. Moreover, it is critical to test the usability and the user experience of application-based neuropsychological assessments within diverse aging adult populations. In this pilot study, verbal expressions of feeling pressure to succeed, within a diverse population of young adults, were examined while taking an application-based neuropsychological assessment. Data was collected from 15 self-identified respondents (i.e., 7 Latinx, 5 Asian, 3 Bi-racial). Before beginning the assessment, 8 out of 15 participants exhibited self-handicapping behaviors such as offering explanations of mental exhaustion due to work and lack of sleep. Literature suggests these expressions are related to the onset of anxiety prior to taking cognitive tests, and contribute to potentially offering an excuse in anticipation of poor performance. Additionally, 3 out of 15 participants noted that even though the tasks were simple, they felt unintelligent because they did not complete the tasks to their best abilities (e.g., “I felt stupid. It was simple”). Findings from this pilot support the negative impact stereotype threats have on feelings of inadequacy and increase of anxiety levels among ethnic minorities in testing settings. Further emphases on examining the usability and user experience of application-based tests are needed, particularly within a diverse population of aging adults to facilitate more culturally competent neuropsychological testing experiences.