A heuristic approach to solve an integrated ...
Type de document :
Autre communication scientifique (congrès sans actes - poster - séminaire...): Communication dans un congrès avec actes
Titre :
A heuristic approach to solve an integrated warehouse order picking problem
Auteur(s) :
Ogier, Maxime [Auteur]
Integrated Optimization with Complex Structure [INOCS]
Bué, Martin [Auteur]
Inria Lille - Nord Europe
Cattaruzza, Diego [Auteur]
Integrated Optimization with Complex Structure [INOCS]
Semet, Frédéric [Auteur]
Integrated Optimization with Complex Structure [INOCS]
Integrated Optimization with Complex Structure [INOCS]
Bué, Martin [Auteur]
Inria Lille - Nord Europe
Cattaruzza, Diego [Auteur]
Integrated Optimization with Complex Structure [INOCS]
Semet, Frédéric [Auteur]
Integrated Optimization with Complex Structure [INOCS]
Titre de la manifestation scientifique :
IFORS 2017, 21st Conference of the International Federation of Operational Research Societies
Ville :
Québec
Pays :
Canada
Date de début de la manifestation scientifique :
2017-07-16
Mot(s)-clé(s) en anglais :
Warehouse management
order batching
picker routing
order batching
picker routing
Discipline(s) HAL :
Sciences cognitives/Informatique
Computer Science [cs]/Operations Research [math.OC]
Computer Science [cs]/Operations Research [math.OC]
Résumé en anglais : [en]
In this abstract we address an integrated warehouse order picking problem.The warehouse is divided in the picking and the storage areas.We focus on the picking area. It contains a set of aisles, each composed by a set of ...
Lire la suite >In this abstract we address an integrated warehouse order picking problem.The warehouse is divided in the picking and the storage areas.We focus on the picking area. It contains a set of aisles, each composed by a set of storage positions. For each period of the working day each position contains several pieces of a unique product, defined by its reference.The warehouse is not automated, and the order pickers can prepare up to K parcels in a given picking route.For each period of the working day a set of customers orders is received at the warehouse. An order is a set of product references, each associated with a quantity, i.e. the number of pieces required.The problem consists in jointly deciding:(1) the assignment of references to storage positions in the aisles which need to be filled up;(2) the division of orders into several parcels, respecting weight and size constraints;(3) the batching of parcels into groups of size K, that implicitly define the routing into the picking area.The routing is assumed to follow a return policy, i.e. an order picker enters and leaves each aisle from the same end.The objective function is to minimize the total routing cost.In order to deal with industrial instances of large size (considering hundreds of clients, thousands of positions and product references) in a short computation time, a heuristic method based on the split and dynamic programming paradigms is proposed.Experimental results will be presented.Lire moins >
Lire la suite >In this abstract we address an integrated warehouse order picking problem.The warehouse is divided in the picking and the storage areas.We focus on the picking area. It contains a set of aisles, each composed by a set of storage positions. For each period of the working day each position contains several pieces of a unique product, defined by its reference.The warehouse is not automated, and the order pickers can prepare up to K parcels in a given picking route.For each period of the working day a set of customers orders is received at the warehouse. An order is a set of product references, each associated with a quantity, i.e. the number of pieces required.The problem consists in jointly deciding:(1) the assignment of references to storage positions in the aisles which need to be filled up;(2) the division of orders into several parcels, respecting weight and size constraints;(3) the batching of parcels into groups of size K, that implicitly define the routing into the picking area.The routing is assumed to follow a return policy, i.e. an order picker enters and leaves each aisle from the same end.The objective function is to minimize the total routing cost.In order to deal with industrial instances of large size (considering hundreds of clients, thousands of positions and product references) in a short computation time, a heuristic method based on the split and dynamic programming paradigms is proposed.Experimental results will be presented.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Collections :
Source :