partial reinforcement optimizer (PRO). Matlab Source Code

This source code is an implementation of the PRO algorithm to solve CEC2017 benchmark functions.

Partial Reinforcement Optimizer (PRO), is a novel evolutionary optimization algorithm. The major idea behind the PRO comes from a psychological theory in evolutionary learning and training called the partial reinforcement effect (PRE) theory. According to the PRE theory, a learner is intermittently reinforced to learn or strengthen a specific behavior during the learning and training process. The reinforcement patterns significantly impact the response rate and strength of the learner during a reinforcement schedule, achieved by appropriately selecting a reinforcement behavior and the time of applying reinforcement process. In the PRO algorithm, the PRE theory is mathematically modeled to an evolutionary optimization algorithm for solving global optimization problems.