A HYBRID ALGORITHM FOR THE UNCERTAIN INVERSE p-MEDIAN LOCATION PROBLEM

In this paper, we investigate the inverse p-median location  problem with variable edge lengths and variable vertex weights on networks in which the vertex weights and modification costs are the independent uncertain variables. We propose a  model for the uncertain inverse p-median location problem  with tail value at risk objective. Then, we show that  it  is NP-hard. Therefore,  a hybrid particle swarm optimization  algorithm is presented  to obtain   the approximate optimal solution of the proposed model. The algorithm contains expected value simulation and tail value at risk simulation

A SOLUTION ALGORITHM FOR p-MEDIAN LOCATION PROBLEM ON UNCERTAIN RANDOM NETWORKS

This paper investigatesthe classical $p$-median location problem in a network in which some of the vertex weights and the distances between vertices are uncertain and while others are random. For solving the $p$-median problem in an uncertain random network, an optimization model based on the chance theory is proposed first and then an algorithm is presented to find the $p$-median. Finally, a numerical example is given to illustrate the efficiency of the proposed metho

A MODIFIED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR GENERAL INVERSE ORDERED p-MEDIAN LOCATION PROBLEM ON NETWORKS

This paper is concerned with a general inverse ordered p-median location problem on network where the task is to change (increase or decrease) the edge lengths and vertex weights at minimum cost subject to given modification bounds such that a given set of p vertices becomes an optimal solution of the location problem, i.e., an ordered p-median under the new edge lengths and vertex weights. A modified particle swarm optimization algorithm is designed to solve the problem under the cost functions related to the sum-type Hamming, bottleneck-type Hamming distances and the recti-linear and Chebyshev norms. By computational experiments, the high efficiency of the proposed algorithm is illustrated

Influence of “Nicoflok” Polymer-Mineral with Portland Cement on Granular Soils and Recycled Asphalt Material

In road construction projects, due to the high volume of soil materials, the costs of supplying and transporting high-quality materials are very high, they may also include the crossing between different geotechnical lands with different types of soils and soil stabilization used to modify resistance characteristics of soil materials in different layers of the road. Addition of a stabilizing agent can improve the properties of aggregates and subgrade soils. In this study, the effect caused by the combined action of polymer-mineral composition “Nicoflok” and cement stabilization on the strength characteristics and durability of local materials, adopted from under-construction Ilkhchi highway project, was investigated. In addition, the effects of stabilizers on the recycled asphalt materials was studied to assess the possibility of using them in the pavement structure. Samples with 0, 0.5, 0.9 and 1.3 percent of Nicoflok combined with varying percentages of cement content were made and CBR tests were conducted after curing. Strength degradation of samples under 50 cycles of freeze-thaw was also investigated. The results show that addition of cement- Nicoflok admixture to the subgrade soil considerably increases CBR values, which leads to reduction of the required material amount. The efficiency of this polymer with Portland cement depends on several factors, such as the amount of cement, curing time, size and shape of soil grains. The optimum dosage of Nicoflok was 0.9% mixed with 1% cement. Stabilizing the base and recycled asphalt materials with cement and Nicoflok also improves the long-term performance of the pavement

Learning Approaches of Undergraduate Nursing and Midwifery Students: A Longitudinal Study

Introduction: Development of advanced learning along with students’ progress is one of the main goals of higher education and learning approaches act as a key concept. Therefore, it is very important to understand how students’ learning approaches change over time. The aim of this study was to investigate the learning approaches of undergraduate nursing and midwifery students during their studies at Bushehr University of Medical Sciences. Methods: This descriptive-longitudinal study was conducted from 2012-16. A total of 76 undergraduate nursing and midwifery students who entered Bushehr University of Medical Sciences were selected by means of census method. Learning approaches of the students were measured using the Persian version of Revised Two-Factor Study Process Questionnaire whose validity and reliability were confirmed. Data were analyzed using descriptive statistics, independent t-test and ANOVA. Results: Findings showed that the majority of students used the deep learning approach (29.81±7.234, total=???) throughout their studying years. However, ANOVA test did not show a statistically significant difference between surface and deep learning approaches scores of nursing (p=0.109, p=0.481) and midwifery (p=0.232, p=0.328) students in terms of the years of study. Although, independent t-test showed a statistically significant difference in employing the surface learning approach in terms of the field of study (p=0.02) and gender (p=0.001). Conclusion: Although deep learning was the dominant approach, there was no change in the students’ learning approaches in higher years of education. Therefore, given the focus of higher education on developing the deep learning approach in students and the importance of medical science fields for society, it is necessary for teachers, managers and educational planners to assess the deep learning approach