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Local search heuristics for the identical parallel machine scheduling with transport robots

Alexander Yuskov, Yury Kochetov


We consider a new scheduling problem originating from order picking at an automatic warehouse. We have a finite set of orders. Each order consists of a set of items. All orders should process through the picking stage, where items are extracted from pallets and packed in boxes for customers. We have some identical parallel picking machines and some parking slots for pallets. Each machine can use the pallets from all parking slots. Each pallet should be brought from the automatic warehouse to the parking slot and returned by a transport robot. The fleet of robots is limited. Our goal is to process all orders with minimal makespan. To tackle the problem, we design a mathematical model and three local search heuristics based on the order permutations. A fast decoder procedure creates an active schedule for parallel machines under the robot fleet constraint. Computational experiments for semi-synthetic test instances with up to 345 orders, 30 robots, and 16 parallel machines indicate the high efficiency of the approach.


machine scheduling, transport robot, local search, order picking.

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