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Comparison of MOEAs in an Optimization-Decision Methodology for a Joint Order Batching and Picking System

Author

Listed:
  • Fabio Maximiliano Miguel

    (Sede Alto Valle y Valle Medio, Universidad Nacional de Río Negro, CONICET, Villa Regina 8336, Argentina
    These authors contributed equally to this work.)

  • Mariano Frutos

    (Departamento de Ingeniería, Universidad Nacional del Sur, IIESS UNS-CONICET, Bahía Blanca 8000, Argentina
    These authors contributed equally to this work.)

  • Máximo Méndez

    (Instituto Universitario SIANI, Universidad de Las Palmas de Gran Canaria (ULPGC), 35017 Las Palmas de Gran Canaria, Spain
    These authors contributed equally to this work.)

  • Fernando Tohmé

    (Departamento de Economía, Universidad Nacional del Sur, INMABB UNS-CONICET, Bahía Blanca 8000, Argentina
    These authors contributed equally to this work.)

  • Begoña González

    (Instituto Universitario SIANI, Universidad de Las Palmas de Gran Canaria (ULPGC), 35017 Las Palmas de Gran Canaria, Spain
    These authors contributed equally to this work.)

Abstract

This paper investigates the performance of a two-stage multi-criteria decision-making procedure for order scheduling problems. These problems are represented by a novel nonlinear mixed integer program. Hybridizations of three Multi-Objective Evolutionary Algorithms (MOEAs) based on dominance relations are studied and compared to solve small, medium, and large instances of the joint order batching and picking problem in storage systems with multiple blocks of two and three dimensions. The performance of these methods is compared using a set of well-known metrics and running an extensive battery of simulations based on a methodology widely used in the literature. The main contributions of this paper are (1) the hybridization of MOEAs to deal efficiently with the combination of orders in one or several picking tours, scheduling them for each picker, and (2) a multi-criteria approach to scheduling multiple picking teams for each wave of orders. Based on the experimental results obtained, it can be stated that, in environments with a large number of different items and orders with high variability in volume, the proposed approach can significantly reduce operating costs while allowing the decision-maker to anticipate the positioning of orders in the dispatch area.

Suggested Citation

  • Fabio Maximiliano Miguel & Mariano Frutos & Máximo Méndez & Fernando Tohmé & Begoña González, 2024. "Comparison of MOEAs in an Optimization-Decision Methodology for a Joint Order Batching and Picking System," Mathematics, MDPI, vol. 12(8), pages 1-23, April.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:8:p:1246-:d:1379273
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    References listed on IDEAS

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