https://www.cirrelt.ca/DocumentsTravail/CIRRELT-2011-62.pdf

A review of dynamic vehicle routing problems

Acknowledgments vii Preface xiii Chapter 1. Educational Attainment: Overall Trends, Disparities, and the Public Universities We Study 1 Chapter 2. Bachelor's Degree Attainment on a National Level 20 Chapter 3. Finishing College at Public Universities 32 Chapter 4. Fields of Study, Time-to-Degree, and College Grades 57 Chapter 5. High Schools and "Undermatching" 87 Chapter 6. Test Scores and High School Grades as Predictors 112 Chapter 7. Transfer Students and the Path from Two-Year to Four-Year Colleges 134 Chapter 8. Financial Aid and Pricing on a National Level 149 Chapter 9. Financial Aid at Public Universities 166 Chapter 10. Institutional Selectivity and Institutional Effects 192 Chapter 11. Target Populations 207 Chapter 12. Looking Ahead 223 Appendix A. The Modern Evolution of America's Flagship Universities by Eugene M. Tobin 239 Notes 265 List of Figures 337 List of Tables 347 List of Appendix Tables 349 References 357 Index 377

Crossing the Finish Line:: Completing College at America’s Public Universities (Association for Institutional Research, May 30, 2010)

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Boosting: Foundations and Algorithms.

The vehicle routing problem with drones (VRPD) is an extension of the classic capacitated vehicle routing problem, where not only trucks but drones are used to deliver parcels to customers. One distinctive feature of the VRPD is that a drone may travel with a truck, take off from its stop to serve customers, and land at a service hub to travel with another truck as long as the flying range and loading capacity limitations are satisfied. Routing trucks and drones in an integrated manner makes the problem much more challenging and different from classical vehicle routing literature. We propose a mixed integer programming model, and develop a branch-and-price algorithm. Extensive experiments are conducted on the instances randomly generated in a practical setting, and the results demonstrate the good computational performance of the proposed algorithm. We also conduct sensitivity analysis on a key factor that may affect the total cost of a solution.

Vehicle routing problem with drones

City Logistics Centers (CLC) are an important part of the modern urban logistics system, and the selection of the location of a CLC has become a key problem in logistics and supply chain management. Integrating the economic, environmental, and social dimensions of sustainable development, this paper presents a new evaluation system for the location selection of a CLC from a sustainability perspective. A fuzzy multi-attribute group decision making (FMAGDM) technique based on a linguistic 2-tuple is used to evaluate potential alternative CLC locations. In this method, the linguistic evaluation values of all the evaluation criteria are transformed into linguistic 2-tuples. A new 2-tuple hybrid ordered weighted averaging (THOWA) operator is presented to aggregate the overall evaluation values of all experts into a collective evaluation value for each alternative, which is then used to rank and select alternative CLC locations. An application example is provided to validate the method developed and to highlight the implementation, practicality, and effectiveness by comparing with the fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method.

Location selection of city logistics centers under sustainability

A branch-and-price algorithm for the capacitated facility location problem

To successfully reduce student attrition, it is imperative to understand what the underlying determinants of attrition are and which students are at risk of dropping out. We develop an early detection system (EDS) using administrative student data from a state and a private university to predict student success as a basis for a targeted intervention. The EDS uses regression analysis, neural networks, decision trees, and the AdaBoost algorithm to identify student characteristics which distinguish potential dropouts from graduates. Prediction accuracy at the end of the first semester is 79% for the state university and 85% for the private university of applied sciences. After the fourth semester, the accuracy improves to 90% for the state university and 95% for the private university of applied sciences.

Early Detection of Students at Risk – Predicting Student Dropouts Using Administrative Student Data and Machine Learning Methods

This paper presents a simple branch-and-bound method based on Lagrangean relaxation and subgradient optimization for solving large instances of the capacitated facility location problem (CFLP) to optimality. To guess a primal solution to the Lagrangean dual, we average solutions to the Lagrangean subproblem. Branching decisions are then based on this estimated (fractional) primal solution. Extensive numerical results reveal that the method is much faster and more robust than other state-of-the-art methods for solving the CFLP exactly.

https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.1110.0468/suppl_file/ijoc.1110.0468-sm-online-supplement.pdf

A Simple but Usually Fast Branch-and-Bound Algorithm for the Capacitated Facility Location Problem

On-line routing is concerned with building vehicle routes in an on-going fashion in such a way that customer requests arriving dynamically in time are efficiently and effectively served. An indispensable prerequisite for applying on-line routing methods is mobile communication technology. Additionally it is of utmost importance that the employed communication system is suitable integrated with the firm’s enterprise application system and business processes. On basis of a case study, we describe in this paper a system that is cheap and easy to implement due to the use of simple mobile phones. Additionally, we address the question how on-line routing methods can be integrated in this system.

On line Routing per Mobile Phone A Case on Subsequent Deliveries of Newspapers

The single-sink fixed-charge transportation problem (SSFCTP) consists of finding a minimum cost flow from a number of nodes to a single sink. Beside a cost proportional to the amount shipped, the flow cost encompass a fixed charge. The SSFCTP is an important subproblem of the well-known fixed-charge transportation problem. Nevertheless, just a few methods for solving this problem have been proposed in the literature. In this paper, some greedy heuristic solutions methods for the SSFCTP are investigated. It is shown that two greedy approaches for the SSFCTP known from the literature can be arbitrarily bad, whereas an approximation algorithm proposed in the literature for the binary min-knapsack problem has a guaranteed worst case bound if adapted accordingly to the case of the SSFCTP.

/pdf/analysis-of-some-greedy-algorithms-for-the-single-sink-fixed-2p20xzmhg4.pdf

Analysis of some greedy algorithms for the single-sink fixed-charge transportation problem

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