Metaheuristic approaches in optimizing order picking processes

In manual warehouses, which have an important place in the supply chain, 55% of the cost incurred is due to order picking processes. In high-level warehouses, both electric forklifts and people play a leading role. The increasing interest in energy and ergonomic working conditions is also reflected in warehousing processes. For this reason, this thesis approaches the location assignment, order batching and picker routing processes of manual high-level warehouses from sustainability and ergonomic perspectives. First, an ABC class location assignment policy is proposed to minimize electrical energy and human energy. In the second stage, an order grouping and picker routing mathematical model is proposed for electricity and human energy minimization. Simulated annealing algorithm, genetic algorithm, dragonfly algorithm and their hybrid implementations are also used for the order batching and routing problem. The energy-based ABC class location assignment gave better results than the random location assignment method. The order batching and routing mathematical model also outperformed FCFS batching and s-shaped routing. The dragonfly algorithm and its hybrid methods produced better results than the other algorithms.