Optimization and Learning

Optimization and Learning.- Evolutionary-Based Co-Optimization of DNN and Hardware Configurations on Edge GPU.- Maximum Information Coverage and Monitoring Path Planning With Unmanned Surface Vehicles Using Deep Reinforcement Learning.- Tuning ForestDisc hyperparameters: A sensitivity analysis.- Multi-objective hyperparameter optimization with performance uncertainty.- Novel Optimization Techniques.- A new algorithm for bi-objective problems based on gradient information.- Adaptive Continuous Multi-Objective Optimization using Cooperative Agents.- Integer Linear Programming reformulations for the linear ordering problem.- SHAMan: a versatile auto-tuning framework for costly and noisy HPC systems.- Cooperation-based search of global optima.- Date-driven Simulation-Optimization (DSO): An Efficient Approach to Optimize Simulation Models with Databases.- Logistics.- Sweep Algorithms for the Vehicle Routing Problem with TimeWindows.- Improving the accuracy of vehicle routing problem approximation using the formula for the average distance between a point and a rectangular area.- Optimal Delivery Area Assignment for the Capital Vehicle Routing Problem Based on a Maximum Likelihood Approach.- Neural Order-First Split-Second Algorithm for the Capacitated Vehicle Routing Problem.- Applications.- GRASP-based hybrid search to solve the multi-objective requirements selection problem.- Comparing Parallel Surrogate-based and Surrogate-free Multi-Objective Optimization of COVID-19 vaccines allocation.- Decentralizing and Optimizing Nation-Wide Employee Allocation while Simultaneously Maximizing Employee Satisfaction.- Categorical-Continuous Bayesian optimization applied to chemical reactions.- Assessing Similarity-Based Grammar-Guided Genetic Programming Approaches for Program Synthesis.