Metaheuristic scheduling of multiple picking agents for warehouse management

Purpose – This paper aims to develop a scheduler for multiple picking agents in a warehouse that takes into account distance and loading queue delay minimization within the context of minimizing makespan (i.e. picking time).Design/methodology/approach – The paper uses tabu search to solve the scheduling problem in a more global sense. Each search iteration is enhanced by a custom local search (LS) procedure that hastens convergence by driving a given schedule configuration quickly to a local minimum. In particular, basic operators transfer demand among agents to balance load and minimize makespan. The new load distribution is further improved by considering a vehicle‐routing problem on the picking assignments of the agents with relocated demands. Loading queue delays that may arise from the reassignments are systematically minimized using a fast scheduling heuristic.Findings – The proposed tabu scheduler greatly improves over a widely practiced scheduling procedure for the given problem. Variants of the t...

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