Solving the Parallel Pickup Problem for Multiple Machines in Warehouse Applications with Best-First Searches

M. Matusiak and J. Saarinen (Finland)


Warehouse, combinatorial, best-first search, transportation, order picking, sequential ordering problem


In this paper we present methods for evaluating combina tions of bundles of sequentially ordered tasks for allocation to a multi-machine system. Two algorithms, both based on the idea of best-first search are used to solve a ware house transportation application scenario optimally to an extent with regard to total distance traveled within the sys tem. A greedy version of the evaluation algorithm was also tested. The scenario is as follows: there is an order-picking warehouse where trucks come in each with an order of a number of roller cages. Each roller cage must be filled in a predefined order. Offline results and simulations run in a multi-robot simulator with different missions show that while combinatorial task evaluation is a very important fac tor in decreasing the total travel distance during randomly generated missions, there is a point in path size after which it will be more advantageous to use better path planning.

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