Optimal TSP tour length estimation using Sammon maps

Nautical tourism stands out for its potential to achieve social-economic development in coastal and island destinations and as a lever for sustainable tourism. However, the lack of a clear definition of nautical tourism at the international level makes it difficult to characterize it, and the case of Portugal is no exception. In fact, despite the enormous potential of Portuguese nautical tourism, there is a lack of studies that characterize this type of tourism in the Portuguese tourism destination. This paper intends to make a first attempt to fill this gap by assessing the projected destination image of Portuguese nautical tourism with a sustainable marketing approach. In the design of the research, the content analysis methodology was applied. The data were collected from the official websites of the Portuguese legislation and the Portuguese nautical tourism players and analyzed through a theoretical model of sustainable marketing deriving from the literature review. The results provide the sustainable projected destination image of Portuguese nautical tourism and identify the main trends in the legislative framework, tourism activities, networks of players, and support infrastructures for Portuguese nautical tourism. The findings provide practical and useful insights for Portuguese nautical tourism stakeholders aiming to improve a sustainable projected destination image, as well as for researchers identifying research gaps in the nautical tourism topics. This study also provides a new methodological contribution, proposing a theoretical model of the projected destination image of nautical tourism with an approach to sustainable marketing, which can be applied to other nautical tourism destinations.

/pdf/features-of-nautical-tourism-in-portugal-projected-ill12jqb.pdf

Features of Nautical Tourism in Portugal—Projected Destination Image with a Sustainability Marketing Approach

Shared bikes can help cities achieve carbon neutrality goals. Cleaning and disinfection are vital procedures of the maintenance of shared bikes, especially during the COVID-19 pandemic because shared bikes could be a transmission intermediary of viruses. This study proposes an optimization model of the cleaning and disinfection scheme of the dockless shared bikes. The disinfection is assumed to be performed at night, when the usage is lowest. By regarding the disinfection staff as traveling salesmen, the model is formulated as an extension of the Multidepot Multiple Traveling Salesman Problem (MDMTSP). The objective function is to minimize the total cost; which consists of the cost associated with the working time and per-capita cost of the disinfection staff. A heuristic algorithm combining 
 
 k
 
 -means clustering and genetic algorithm (K-GA) is adopted to find the lower bound solution. Then, the K-GA-adjustment algorithm has been adopted to find the solutions that satisfy the constraints. To reduce the computing time needed, an approximate function for the lower bound of the optimal number of disinfection staff is obtained by constructing a Continuous Approximation (CA) model. A case study based on real location data of shared bikes in Chengdu, China, is performed to show how the maintenance department could adopt the optimization framework to design an efficient scheme to clean and disinfect the shared bikes.

Optimizing the Cleaning and Disinfection Scheme for Dockless Shared Bikes

The education system has a serious challenge when teachers leave their positions or are not replaced quickly enough. This might have a negative effect on the students' learning outcomes. Salary and benefits, working conditions, school culture, peer support, teacher-to-teacher collaboration, and individual and family circumstances are only few of the elements that might affect teacher retention and turnover. To combat the problem of teacher attrition and turnover and give educators the resources they need to do their jobs well, a thorough understanding of these variables is crucial. In sum, retaining and replacing teachers is a difficult problem that must be worked on constantly to improve if all children are to have equal access to a good education.

/pdf/teacher-retention-and-turnover-exploring-the-factors-that-2mcaz9k2.pdf

Teacher Retention and Turnover: Exploring the Factors that Influence Teacher Decision-Making

Finding the shortest path of the traveling salesman problem (TSP) is a typical NP-hard problem and one of the basic optimization problems. TSP in three-dimensional space (3D-TSP) is an extension of TSP. It plays an important role in the fields of 3D path planning and UAV inspection, such as forest fire patrol path planning. Many existing studies have focused on the expected length of the shortest path of TSP in 2D space. The expected length of the shortest path in 3D space has not yet been studied. To fill this gap, this research focuses on developing models to estimate the expected length of the shortest path of 3D-TSP. First, different experimental scenarios are designed by combining different service areas and the number of demand points. Under each scenario, the specified number of demand points is randomly generated, and an improved genetic algorithm and Gurobi are used to find the shortest path. A total of 500 experiments are performed for each scenario, and the average length of the shortest path is calculated. The models to estimate the expected length of the shortest path are proposed. Model parameters are estimated and k-fold cross-validation is used to evaluate the goodness of fit. Results show that all the models fit the data well and the best model is selected. The developed models can be used to estimate the expected length of the shortest path of 3D-TSP and provide important references for many applications.

/pdf/expected-length-of-the-shortest-path-of-the-traveling-2hj82gh4.pdf

Expected Length of the Shortest Path of the Traveling Salesman Problem in 3D Space

With the rise of user-generated content (UGC) and deep learning technology, more and more researchers construct and measure the tourism destination image (TDI) through online travelogues. However, due to the impact of COVID-19 prevention and control, the number of online travelogues has decreased significantly and, therefore, the scientific validity of the TDI based only on text or photos has been questioned. This research fills a gap by comparing the differences between visual and semantic images in terms of the overall image perception and image formation through natural language processing technology and image caption technology in obtaining TDIs, taking Tiantai County in Zhejiang Province of China as a case. Our results show that the texts and photographs shared major similarities in the overall TDI, but from the perspective of interest, they reflect differently. Therefore, when considering the data source selection for TDI research with a small number of travelogues, texts should be the main content, supplemented by photographs.

/pdf/reconsidering-tourism-destination-images-by-exploring-kxlac5dm.pdf

Reconsidering Tourism Destination Images by Exploring Similarities between Travelogue Texts and Photographs

In the post pandemic era, most of the countries are facing challenges in economic recovery, while investing in creative human capital such as teachers by increasing their salaries can be one of the policy options for governments to drive development. Housing price, however, may impact the working of these policies. Using the panel data of 31 provincial regions in China during 2006–2018, we evaluated the relationship between housing price, the improvement in teacher salary, and sustainable regional economic development. From the perspective of imbalanced regional development, we discovered the heterogeneity in the rate of return on education investment in terms of teacher salary. Higher teacher salary plays a more active role in the sustainable development of underdeveloped regions, and the crowding-out effect of housing price in Western China is the most intense. The results further provide some policy implications on efficiently promoting the coordinated development of sustainable regional economies by improving the creative human capital cultivators’ salaries. This paper verifies the significance of housing price dynamics from a new perspective based on educational investment. Overall, our study provides theoretical support for improving teachers’ income to promote regional economic development and further provides guidance for the government to carry out macro control to promote regional economic development with changes in housing price dynamics. Our study aims to link land systems, particularly the housing market, to sustainability and public policy.

/pdf/the-relationship-between-housing-price-teacher-salary-34sjk8og.pdf

Xiaoqian Lu

Papers

Expected Length of the Shortest Path of the Traveling Salesman Problem in 3D Space

Reconsidering Tourism Destination Images by Exploring Similarities between Travelogue Texts and Photographs

The Relationship between Housing Price, Teacher Salary Improvement, and Sustainable Regional Economic Development

Optimizing the Cleaning and Disinfection Scheme for Dockless Shared Bikes