Bilevel optimization problems embed the optimality of a subproblem as a constraint of another optimization problem. We introduce the concept of near-optimality robustness for bilevel optimization, protecting the upper-level solution feasibility from limited deviations from the optimal solution at the lower level. General properties and necessary conditions for the existence of solutions are derived for near-optimal robust versions of general bilevel optimization problems. A duality-based solution method is defined when the lower level is convex, leveraging the methodology from the robust and bilevel literature. Numerical results assess the efficiency of exact and heuristic methods and the impact of valid inequalities on the solution time.

In blockchains , transaction fees are fixed by the users. The probability for a transaction to be processed quickly increases with the fee level. In this paper, we study the transaction fee optimization problem in the Ethereum blockchain. This problem consists of determining the minimum price a user should pay so that its transaction is processed with a given probability in a given amount of time. To reach this goal, we define a new solution method based on a Monte Carlo approach to predict the probability that a transaction will be mined within a given time limit. Numerical results on real data highlight the quality of the results.

Along with many ASCILITE members, we have grown increasingly concerned that current approaches to \neducational technology research lack value and practical application in the field. Educational design \nresearch (EDR) is an emerging approach that bridges the demand for rigorous research with the \ndevelopment of relevant solutions to educational problems. EDR is an intervention and process-oriented \napproach that uses a variety of methods to examine the development and implementation of instructional \nsolutions to current educational problems. As evidence about the inner workings of interventions \naccumulates over time, design principles and learning theories are derived from work in local contexts, and \ntheir limits can be tested in other settings. This genre of research is currently underrepresented in the \nliterature. To advance scholarship through the execution and reporting of EDR, we identified an urgent \nneed for examples across fields, and especially related to educational technology in higher education.