This book constitutes the refereed proceedings of the 5th International Conference on Optimization and Learning, OLA 2022, which took place in Syracuse, Sicilia, Italy, in July 2022. The papers are organized in the following topical sections: 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.