In this work we present our positive experience with a unique advanced job scheduler which we have developed for the widely used TORQUE Resource Manager. Unlike common schedulers using queuing approach and simple heuristics, our solution uses planning (job schedule construction) and schedule optimization by a local search-inspired metaheuristic. Using both complex simulations and practical deployment in a real system, we show that this approach increases predictability, performance and fairness with respect to a common queue-based scheduler. Presented scheduler has been successfully used in the production infrastructure of the Czech Centre for Education, Research and Innovation in ICT (CERIT Scientific Cloud) since July 2014.