This paper describes a hybrid approach to solving large-scale constraint satisfaction and optimization problems. It describes a hybrid algorithm for integer linear programming which combines local search and bounds propagation, inspired by the success of a randomized algorithm for Boolean Satisfiability (SAT) called Unit-Walk. A dynamic prioritization heuristic has been developed to improve the algorithm, inspired by another algorithm called Squeaky Wheel Optimization.