CE10 - Usine du futur : Homme, organisation, technologies

Decision system for smart management of resources in warehouses – AGIRE

Decision system for smart management of resources in warehouses

The project AGIRE addresses the human resources management in warehouses which supply either sale points (B2B) or final consumers (B2C). Such warehouses are under pressure due to the no inventory policy at the sale points and to the constant growth of e-commerce sales. In terms of logistics, this translates into an increasing number of parcels to prepare and to ship to satisfy an order, which is known typically a few hours in advance.

Innovative human-centered decision support tools for warehouse management

Designing an efficient, reactive warehouse able to respond to demand variations is a significant challenge to address. A fully automated warehouse cannot be considered as a solution. Indeed, the investments required to satisfy appropriately demand peaks are too large to be considered. A more suitable approach is to combine human operators equipped with high technology devices and partially automated logistic equipments. However, to better manage human resources in such a dynamic environment, innovative decision support methods have to be designed with the objective of maximizing the welfare of workers while guaranteeing the efficiency of the whole logistics system. This is precisely the central objective of this research project. <br /> <br />AGIRE aims at proposing innovative human-centered decision support tools for warehouse management. Warehouse management problems have been widely studied for decades, but only few works integrate human factors when facing a dynamic demand. This project will explicitly consider these two aspects in the proposed models and algorithms. The main scientific challenges are: (1) the modeling of human and social aspects (e.g. ergonomics, pain/fatigue, congestion); (2) the integration of these human related criteria into optimization models and algorithms, (3) data analysis (e.g. demand forecast) and integration of the uncertainties into the models and solution methods, (4) integration of tactical and operational problems, and (5) solving large-sized instances: a warehouse usually contains hundreds of employees, thousands of storage locations, up to one hundred thousand products to pick each day.

In this 4-year project, we aim at developing innovative intelligent human-centered decision support tools for warehouse management. The proposed methodology relies on an activity analysis to identify and to model the main human factors in warehouse operations. Then, different optimization problems will be addressed at operational and tactical levels (e.g. picker routing, scheduling of picking tours, storage location assignment, workload balancing). These decision levels will be integrated subsequently to ensure that decisions at the tactical level are consistent with the human factors at the operational level. In order to evaluate the obtained solutions, simulation tools will be developed, as well as experiments with feedbacks of users inside the warehouse of Jules.

A state of the art dealing with the integration of human factors in the optimization of supply chains has been conducted. In addition, interviews have been conducted with HappyChic employees in order to specify the process and the organization of the warehouse, the IT tools available to the agents, the management of internal human resources. Different workstations have been identified for the carrying of heavy loads, repeated uncomfortable postures, frequent trips and rotation of the trunk. In addition to the exploratory interviews, visits have been made to the HappyChic warehouse to conduct semi-structured interviews, visits of different areas of the warehouse, and open observations.

In addition, initial works have been initiated on optimization problems in warehouses at the operational and tactical levels.

On the one hand, we study the consideration of congestion in the aisles of the order picking area: congestion occurs when several pickers are in the same aisle (or part of an aisle) during a given time interval. The problem studied is the integrated order batching and picker routing problem. A mathematical model that integrates congestion has been developed and is currently being validated.

On the other hand, we study the modeling of a storage location assignment problem in a logistic warehouse. The goal is to assign products to locations with the objective of minimizing the total distance traveled by the pickers. Several models have been developed in order to represent the different routing policies of a warehouse. In order to solve these optimization problems, a Branch-and-Price algorithm has been designed. This algorithm is under development and the first results are very promising

From the results of the interviews and visits in the warehouse of HappyChic, a new visit on site will be carried out in order to conduct systematic observations of several operators, which will present different profiles. These observations will allow to specify the main human factors to integrate in the studied optimization problems.

Thibault PRUNET, Nabil ABSI, Valeria BORODIN, Diego CATTARUZZA, Storage Location Assignment Problem in Fast Pick Areas: A novel formulation and decomposition method, CPAIOR’2021, Vienna Austria, July 2021.

Thibault PRUNET, Nabil ABSI, Valeria BORODIN, Diego CATTARUZZA, Storage Location Assignment in Fast Pick Area: A column generation approach, ROADEF’2021, Mulhouse France, February 2021.

The project AGIRE addresses the human resources management in warehouses which supply either sale points (B2B) or final consumers (B2C). Such warehouses are under pressure due to the no inventory policy at the sale points and to the constant growth of e-commerce sales. In terms of logistics, this translates into an increasing number of parcels to prepare and to ship to satisfy an order, which is known typically a few hours in advance.

Therefore, designing an efficient, reactive warehouse able to respond to demand variations is a significant challenge to address. A fully automated warehouse cannot be considered as a solution. Indeed, the investments required to satisfy appropriately demand peaks are too large to be considered. A more suitable approach is to combine human operators equipped with high technology devices and partially automated logistic equipments. However, to better manage human resources in such a dynamic environment, innovative decision support methods have to be designed with the objective of maximizing the welfare of workers while guaranteeing the efficiency of the whole logistics system. This is precisely the central objective of this research project.

AGIRE aims at proposing innovative human-centered decision support tools for warehouse management. This will have a tangible impact on the scientific community. Warehouse management problems have been widely studied for decades, but only few works integrate human factors when facing a dynamic demand. This project will explicitly consider these two aspects in the proposed models and algorithms. The main scientific challenges are: (1) the modeling of human and social aspects (e.g. ergonomics, pain/fatigue, congestion); (2) the integration of these human related criteria into optimization models and algorithms, (3) data analysis (e.g. demand forecast) and integration of the uncertainties into the models and solution methods, (4) integration of tactical and operational problems, and (5) solving large-sized instances: a warehouse usually contains hundreds of employees, thousands of storage locations, up to one hundred thousand products to pick each day.

AGIRE is conducted by a consortium of three complementary research teams (INOCS, SFL and SPLOTT) in computer sciences, operations research, and social sciences; and a company in the textile retail: HappyChic. Developed algorithms will be tested on real data collected in the warehouse of the brand Jules of HappyChic.

In this 4-year project, we aim at developing innovative intelligent human-centered decision support tools for warehouse management. The proposed methodology relies on an activity analysis to identify and to model the main human factors in warehouse operations. Then, different optimization problems will be addressed at operational and tactical levels (e.g. picker routing, scheduling of picking tours, storage location assignment, workload balancing). These decision levels will be integrated subsequently to ensure that decisions at the tactical level are consistent with the human factors at the operational level. In order to evaluate the obtained solutions, simulation tools will be developed, as well as experiments with feedbacks of users inside the warehouse of Jules.

Project coordinator

Monsieur Maxime Ogier (Centre de Recherche en Informatique, Signal et Automatique de Lille)

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.

Partner

HAPPYCHIC LOGISTIQUE
CRIStAL Centre de Recherche en Informatique, Signal et Automatique de Lille
EMSE/LIMOS Mines Saint-Etienne/Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes
IFSTTAR / AME / SPLOTT INSTITUT FRANCAIS DES SCIENCES ET TECHNOLOGIES DES TRANSPORTS DE L'AMENAGEMENT ET DES RESEAUX

Help of the ANR 585,381 euros
Beginning and duration of the scientific project: February 2020 - 48 Months

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