An exact algorithm for constrained k-cardinality unbalanced assignment problem

An assignment problem (AP) usually deals with how a set of persons/tasks can be assigned to a set of tasks/persons on a one-to-one basis in an optimal manner. It has been observed that balancing among the persons and jobs in several real-world situations is very hard, thus such scenarios can be seen as unbalanced assignment models (UAP) being a lack of workforce. The solution techniques presented in the literature for solving UAP’s depend on the assumption to allocate some of the tasks to fictitious persons; those tasks assigned to dummy persons are ignored at the end. However, some situations in which it is inevitable to assign more tasks to a single person. This paper addresses a practical variant of UAP called k-cardinality unbalanced assignment problem (k-UAP), in which only of persons are asked to perform jobs and all the persons should perform at least one and at most jobs. The k-UAP aims to determine the optimal assignment between persons and jobs. To tackle this problem optimally, an enumerative Lexi-search algorithm (LSA) is proposed. A comparative study is carried out to measure the efficiency of the proposed algorithm. The computational results indicate that the suggested LSA is having the great capability of solving the smaller and moderate instances optimally.

Locating Organizations and Their Methods in Registrations of Clinical Migraine Trials: Analysis of ClinicalTrials.gov

Background and Objective:ClinicalTrials.gov is a centralized venue for monitoring clinical research and allows access to information on publicly and privately funded studies. To better recognize influential institutions in the field of headache, we identified major organizations conducting clinical trials in migraine research. Furthermore, we examined the frequency of different study designs.Methods: Utilizing the ClinicalTrials.gov application programming interface, we extracted studies including individuals with migraine from February 29, 2000, to July 28, 2020, for the following: (1) host organization, (2) study type, (3) primary purpose, (4) intervention model, and (5) allocation.Results: We included 921 entries encompassing 423 organizations. Thirty-two organizations produced ≥5 entries each and 40.0% of all entries. Most, 86%, were interventional studies while 13.6% were observational studies. The most common study design had a randomized allocation of participants. The most frequent primary purpose was treatment (62.4%) followed by prevention (13.0%). There were 56.9% parallel assignment models, 15.2% single group assignment models, and 12.4% crossover assignment models.Conclusion: A minority of organizations contribute to a significant number of registrations of clinical migraine trials, suggesting that clinical research in migraine is oligarchic. The most common study is interventional and randomized, with parallel assignment of participants with treatment as the primary purpose. This likely reflects the need to evaluate novel putative pharmacological medications.

Progress on error propagation and correction of long-range rockets in disturbing gravity field

Disturbing gravity field is becoming an important factor leading to impact error of long-range rockets. In this paper, the influence mechanism of deflection of the vertical and spatial disturbing gravity on inertial navigation and guidance system are firstly introduced, respectively. Then, the navigation error propagation methods due to disturbing gravity field are reviewed. The fast assignment models of disturbing gravity field, which are available for compensating navigation errors in engineering, are also summarized. After that, the unpowered trajectory error propagation methods and the corresponding guidance correction strategies, as well as potential directions for future efforts, are discussed.

Location, Location, Location? School District, Length of Residence and Attitudes Toward Diversity and Neighborhood Schools in the Upper South

Attitudes toward diversity and neighborhood schools matter because they underlie many families’ decisions for residential location, with consequences for both school systems and students. Case studies of desegregation highlight locational dynamics that influence these outcomes, but differences in theory and methods limit rigorous comparisons among residents across such areas. This study focuses on two under-researched correlates of these preferences toward school assignment models: school district location and length of residence in that district. We evaluate whether school district location and length of residence decrease support for diverse schools and increase support for neighborhood schools, net of numerous controls. We use an innovative new dataset that features opinion polling of respondents’ views of public school assignments in Raleigh, NC; Charlotte, NC; Louisville, KY; Rock Hill, SC; and Nashville, TN (5302 cases). We find that compared to having lived in a school district 7 years or less, living in that district over 15 years decreases support for diversity. Furthermore, living all one’s life in a district increases support for neighborhood schools. We also find that Charlotte-Mecklenburg, Rock Hill, and Nashville districts are less supportive of neighborhood schools than Raleigh, but that there are also interactive effects between length of residence and school district location. These results shed light on district differences in social forces leading to school resegregation.

Learning of Arabic Language Assignment Models for Early Childhood by Online

Learning conducted online during the covid-19 pandemic is also performed at the Early Childhood Education (PAUD) level. Providing online learning for early childhood is not easy because at this age a child should learn many things about physical-motor, moral, emotional, cognitive, language, how to solve problems, and so on that effect throughtout his life, so it is said that this period is the golden age. Giving assignments in online learning is one of the ways that teachers do to monitor the developments of their students. Therefore, this research is about the assignments of early childhood with a focus on Arabic lessons. This research is qualitative methods using observation, interviews, and documentation as research techniques. This research was cinducted at TK-Alfarobi Surabaya with kindergarten B teachers as the main interviews and guardians of students as respondents.. The results of this research show that there are four Arabic assignments performed by the teacher during online learning, there are: 1) a model for increasing competency in Arabic reading and writing; 2) short letter memorization model; 3) the model of memorizing asmaul husna with movements; 4) a model of singing Arabic vocabulary with gestures. Keywords: early childhood education, Arabic Language, Online Learning.

Quantifying the impacts of the modifiable areal unit problem in travel demand models

This project introduces new analyses of the impacts of the modifiable areal unit problem (MAUP) in traffic assignment models which are not widely available in the literature, as well as to reveal how stable the effects are in diverse models. A comprehensive review of the literature is conducted to provide an overview of MAUP, including the scale and zonal effects, as well as its recent applications in travel demand modelling and other subject areas. Particular scrutiny is made towards inappropriate methods of MAUP-analysis in travel demand models. The scale effect is tested in traffic assignment models using associated zone structures of the Greater Montreal Area (GMA), a unique geographic region involving island regions and water bodies.

Quantifying the impacts of the modifiable areal unit problem in travel demand models

This project introduces new analyses of the impacts of the modifiable areal unit problem (MAUP) in traffic assignment models which are not widely available in the literature, as well as to reveal how stable the effects are in diverse models. A comprehensive review of the literature is conducted to provide an overview of MAUP, including the scale and zonal effects, as well as its recent applications in travel demand modelling and other subject areas. Particular scrutiny is made towards inappropriate methods of MAUP-analysis in travel demand models. The scale effect is tested in traffic assignment models using associated zone structures of the Greater Montreal Area (GMA), a unique geographic region involving island regions and water bodies.

A Mathematical Model for In-Person Office Assignment During COVID-19

The global pandemic that is COVID-19 has altered our world as we know it. Educational systems have been seriously affected, businesses – whether “essential” or not – have been severely stressed, how people socialize has, perhaps forever, been changed, and telecommuting is the new norm. The purpose of this paper is to discuss a situation wherein a company was having difficulty in scheduling their in-person office staffing in a move to allow rotational schedules for their employees to decongest their office when an entirely telecommuting operation was not possible. Due to the different types of employees, their various work-related constraints, and the need to minimize the number of bodies in the office while addressing minimum coverage necessary to perform the company’s daily activities, a quick solution to their scheduling/assignment needs was not obvious or trivially obtained. As such, mathematical models, specifically, integer programming assignment models, were developed and ultimately solved using the Python/Gurobi solver to address their scheduling needs. This paper will describe the constraints faced by the company and the models developed to solve their tricky assignment problem.