Operations Research 2025
Abstract Submission

61. An adaptive fix-and-optimize heuristic for solving the integrative zoning and item-to-zone assignment problem in the context of pick-and-pass systems

Invited abstract in session TD-10: Order Picking, stream Supply Chain Management and Production.

Thursday, 14:30-16:00
Room: H16

Authors (first author is the speaker)

1. Regina Thelen
Business Administration Production and Logistics, University of Dortmund
2. Ralf Gössinger
Business Administration, Production and Logistics, University of Dortmund

Abstract

Pick-and-pass systems (P&PS) are zoned order picking systems in which each picker only works in one storage zone and each zone only comprises a sub-set of items. Hence, order-related containers are routed along a sequence of zones to be filled up with the items needed for order fulfillment.
When designing a P&PS, two organizational questions need to be answered: How should the zones be formed and which item should be assigned to which zone? Since both problems are strongly interrelated, we developed a decision model that simultaneously determines zone size and item-to-zone assignment. A numerical pre-study revealed that an exact approach can only solve small prob-lem instances with reasonable computational effort. Since the computational ef-fort of the fix-and-optimize heuristic (FOH) is significantly lower, we expect that problem instances of realistic size can be solved in an acceptable time. Starting from an initial solution, FOH generates smaller sub-problems by iteratively fixing some decision variables, and applies a standard solver to obtain solutions. The best solution to the sub-problems is selected as the solution to the overall problem. In the basic FOH, the problem decomposition is done in advance of the solution process.
In the intended paper, we introduce a new adaptive FOH that decomposes the problem before and during the solution process. This allows the search for better solutions to be controlled depending on the solutions found so far. To assess the performance of this approach, we develop FOH variants and conduct a full-factorial numerical study.

Keywords

Status: accepted

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