A memetic algorithm for the integral OBP/OPP problem in a logistics distribution center

In this paper, we present a new decision-making tool aimed at improving the efficiency of the operational planning of pick-up processes in logistic distribution centers. It is based on a memetic algorithm (MA) solving both the Order Batching Problem (OBP) and the Order Picking Problem (OPP). The result yields a sequence of simultaneous pick up operations of lots for different clients in a storing facility, satisfying a previously defined distribution plan. The objective is the minimization of the operational cost of the entire process, which is directly proportional to the time spent on different activities involved. The failure to satisfy the conditions, either leads to overstocking, delays in delivery or creates inefficiency costs. The analysis of the results obtained with our algorithmic tool indicates that it has a good performance in comparison with other known algorithms used to solve this kind of problem.Fil: Miguel, Fabio. Universidad Nacional de Río Negro; ArgentinaFil: Frutos, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; ArgentinaFil: Tohmé, Fernando Abel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; ArgentinaFil: Rossit, Daniel Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentin

Designing new models and algorithms to improve order picking operations

Order picking has been identified as a crucial factor for the competitiveness of a supply chain because inadequate order picking performance causes customer dissatisfaction and high costs. This dissertation aims at designing new models and algorithms to improve order picking operations and to support managerial decisions on facing current challenges in order picking. First, we study the standard order batching problem (OBP) to optimize the batching of customer orders with the objective of minimizing the total length of order picking tours. We present a mathematical model formulation of the problem and develop a hybrid solution approach of an adaptive large neighborhood search and a tabu search method. In numerical studies, we conduct an extensive comparison of our method to all previously published OBP methods that used standard benchmark sets to investigate their performance. Our hybrid outperforms all comparison methods with respect to average solution quality and runtime. Compared to the state-of-the-art, the hybrid shows the clearest advantages on the larger instances of the existing benchmark sets, which assume a larger number of customer orders and larger capacities of the picking device. Finally, our method is able to solve newly generated large-scale instances with up to 600 customer orders and six items per customer order with reasonable runtimes and convincing scaling behavior and robustness. Next, we address a problem based on a practical case, which is inspired by a warehouse of a German manufacturer of household products. In this warehouse, heavy items are not allowed to be placed on top of light items during picking to prevent damage to the light items. Currently, the case company determines the sequence for retrieving the items from their storage locations by applying a simple S-shape strategy that neglects this precedence constraint. As a result, order pickers place the collected items next to each other in plastic boxes and sort the items respecting the precedence constraint at the end of the order picking process. To avoid this sorting, we propose a picker routing strategy that incorporates the precedence constraint by picking heavy items before light items, and we develop an exact solution method to evaluate the strategy. We assess the performance of our strategy on a dataset provided to us by the manufacturer. We compare our strategy to the strategy used in the warehouse of the case company, and to an exact picker routing approach that does not consider the given precedence constraint. The results clearly demonstrate the convincing performance of our strategy even if we compare our strategy to the exact solution method that neglects the precedence constraint. Last, we investigate a new order picking problem, in which human order pickers of the traditional picker-to-parts setup are supported by automated guided vehicles (AGVs). We introduce two mathematical model formulations of the problem, and we develop a heuristic to solve the NP-hard problem. In numerical studies, we assess the solution quality of the heuristic in comparison to optimal solutions. The results demonstrate the ability of the heuristic in finding high-quality solutions within a negligible computation time. We conduct several computational experiments to investigate the effect of different numbers of AGVs and different traveling and walking speed ratios between AGVs and order pickers on the average total tardiness. The results of our experiments indicate that by adding (or removing) AGVs or by increasing (or decreasing) the AGV speed to adapt to different workloads, a large number of customer orders can be completed until the respective due date

Material handling optimization in warehousing operations

Tableau d’honneur de la Faculté des études supérieures et postdoctorales, 2018-2019.Les activités de distribution et d’entreposage sont des piliers importants de la chaîne d’approvisionnement. Ils assurent la stabilité du flux de matières et la synchronisation de toutes les parties prenantes du réseau. Un centre de distribution (CD) agit comme un point de découplage entre l’approvisionnement, la production et les ventes. La distribution comprend un large éventail d’activités visant à assurer la satisfaction de la demande. Ces activités passent de la réception au stockage des produits finis ou semi-finis, à la préparation des commandes et à la livraison. Les opérations d’un CD sont maintenant perçues comme des facteurs critiques d’amélioration. Elles sont responsables de la satisfaction d’un marché en évolution, exigeant des délais de livraison toujours plus rapides et plus fiables, des commandes exactes et des produits hautement personnalisés. C’est pourquoi la recherche en gestion des opérations met beaucoup d’efforts sur le problème de gestion des CDs. Depuis plusieurs années, nous avons connu de fortes avancées en matière d’entreposage et de préparation de commandes. L’activité de préparation de commandes est le processus consistant à récupérer les articles à leur emplacement de stockage afin d’assembler des commandes. Ce problème a souvent été résolu comme une variante du problème du voyageur de commerce, où l’opérateur se déplace à travers les allées de l’entrepôt. Cependant, les entrepôts modernes comportent de plus en plus de familles de produits ayant des caractéristiques très particulières rendant les méthodes conventionnelles moins adéquates. Le premier volet de cette thèse par articles présente deux importants et complexes problèmes de manutention des produits lors de la préparation des commandes. Le problème de préparation des commandes a été largement étudié dans la littérature au cours des dernières décennies. Notre recherche élargit le spectre de ce problème en incluant un ensemble de caractéristiques associées aux installations physiques de la zone de prélèvement, comme les allées étroites, et aux caractéristiques des produits (poids, volume, catégorie, fragilité, etc.). Une perspective plus appliquée à la réalité des opérations est utilisée dans notre développement d’algorithmes. Les déplacements liés à la préparation des commandes sont fortement influencés par le positionnement des produits. La position des produits dans la zone de prélèvement est déterminée par une stratégie d’affectation de stockage (storage assignment strategy). Beaucoup de ces stratégies utilisent de l’information sur les ventes des produits afin de faciliter l’accès aux plus populaires. Dans l’environnement concurrentiel d’aujourd’hui, la durée de vie rentable d’un produit peut être relativement courte. Des promotions peuvent également être faites pour pousser différents produits sur le marché. Le positionnement fourni par la stratégie d’hier ne sera probablement plus optimal aujourd’hui. Il existe plusieurs études mesurant l’impact d’une bonne réaffectation de produits sur les opérations de prélèvement. Cependant, ils étudient la différence des performances avec les positionnements passés et actuels. La littérature démontre clairement que cela apporte des avantages en termes d’efficacité. Toutefois, les déplacements nécessaires pour passer d’une position à une autre peuvent constituer une activité très exigeante. Ceci constitue le second volet de cette thèse qui présente des avancées intéressantes sur le problème de repositionnement des produits dans la zone de prélèvement. Nous présentons le problème de repositionnement des produits sous une forme encore peu étudiée aux meilleurs de nos connaissances : le problème de repositionnement. Plus précisément, nous étudions la charge de travail requise pour passer d’une configuration à l’autre. Cette thèse est structuré comme suit. L’introduction présente les caractéristiques et les missions d’un système de distribution. Le chapitre 1 fournit un survol de la littérature sur les principales fonctions d’un centre de distribution et met l’accent sur la préparation des commandes et les décisions qui affectent cette opération. Le chapitre 2 est consacré à l’étude d’un problème de préparation de commandes en allées étroites avec des équipements de manutention contraignants. Dans le chapitre 3, nous étudions un problème de préparation des commandes où les caractéristiques des produits limitent fortement les routes de prélèvement. Le chapitre 4 présente une variante du problème de repositionnement (reassignment) avec une formulation originale pour le résoudre. La conclusion suit et résume les principales contributions de cette thèse. Mots clés : Préparation des commandes, entreposage, problèmes de routage, algorithmes exacts et heuristiques, réaffectation des produits, manutention.Distribution and warehousing activities are important pillars to an effective supply chain. They ensure the regulation of the operational flow and the synchronization of all actors in the network. Hence, distribution centers (DCs) act as crossover points between the supply, the production and the demand. The distribution includes a wide range of activities to ensure the integrity of the demand satisfaction. These activities range from the reception and storage of finished or semi-finished products to the preparation of orders and delivery. Distribution has been long seen as an operation with no or low added value; this has changed, and nowadays it is perceived as one of the critical areas for improvement. These activities are responsible for the satisfaction of an evolving market, requiring ever faster and more reliable delivery times, exact orders and highly customized products. This leads to an increased research interest on operations management focused on warehousing. For several years, we have witnessed strong advances in warehousing and order picking operations. The order picking activity is the process of retrieving items within the storage locations for the purpose of fulfilling orders. This problem has long been solved as a variant of the travelling salesman problem, where the order picker moves through aisles. However, modern warehouses with more and more product families may have special characteristics that make conventional methods irrelevant or inefficient. The first part of this thesis presents two practical and challenging material handling problems for the order picking within DCs. Since there are many research axes in the field of warehousing operations, we concentrated our efforts on the order picking problem and the repositioning of the products within the picking area. The order picking problem has been intensively studied in the literature. Our research widens the spectrum of this problem by including a set of characteristics associated with the physical facilities of the picking area and characteristics of the product, such as its weight, volume, category, fragility, etc. This means that a more applied perspective on the reality of operations is used in our algorithms development. The order picking workload is strongly influenced by the positioning of the products. The position of products within the picking area is determined by a storage assignment strategy. Many of these strategies use product sales information in order to facilitate access to the most popular items. In today’s competitive environment, the profitable lifetime of a product can be relatively short. The positioning provided by yesterday’s assignment is likely not the optimal one in the near future. There are several studies measuring the impact of a good reassignment of products on the picking operations. However, they study the difference between the two states of systems on the picking time. It is clear that this brings benefits. However, moving from one position to another is a very workload demanding activity. This constitutes the second part of this thesis which presents interesting advances on the repositioning of products within the picking area. We introduce the repositioning problem as an innovative way of improving performance, in what we call the reassignment problem. More specifically, we study the workload required to move from one setup to the next. This thesis is structured as follows. The introduction presents the characteristics and missions of a distribution system. Chapter 1 presents an overview of the literature on the main functions of a DC and emphasizes on order picking and decisions affecting this operation. Chapter 2 is devoted to the study of a picking problem with narrow aisles facilities and binding material handling equipment. In Chapter 3, we study the picking problem with a set of product features that strongly constrain the picking sequence. Chapter 4 presents a variant of the reassignment problem with a strong and new formulation to solve it. The conclusion follows and summarizes the main contributions of this thesis. Key words: Order-picking, warehousing, routing problems, exact and heuristic algorithms, products reassignment, material handling

Order picking in parallel-aisle warehouses with multiple blocks::complexity and a graph theory-based heuristic

In this paper, we consider the order picking problem (OPP), which constitutes one of the special cases of the Steiner travelling salesperson problem and addresses the costliest operation in a warehouse. Given a list of items to be picked and their locations in the warehouse layout, the OPP aims to find the shortest route that starts from a depot point, picks all the items in the list, and returns to the depot. This paper fills two important gaps regarding the OPP. First, to the best of our knowledge, we present the first complexity results on the problem. Second, we propose a heuristic approach that makes use of its graph-theoretic properties. Computational experiments on randomly generated instances show that the heuristic not only outperforms its state-of-the-art counterparts in the literature, but it is also robust in terms of changing problem parameters

Desenvolvimento de uma metodologia baseada em um modelo exato para resolver o picker routing problem em um caso real

Orientador: Prof. Dr. Cassius Tadeu ScarpinDissertação (mestrado) - Universidade Federal do Paraná, Setor de Ciências Sociais Aplicadas, Programa de Pós-Graduação em Gestão de Organizações, Liderança e Decisão. Defesa : Curitiba, 14/10/2022Inclui referênciasResumo: Neste trabalho apresenta-se uma aplicação real de um modelo exato para o Problema de Roteamento de Separadores de Pedidos, também conhecido com Picker Routing Problem (PRP), em uma Rede varejista do setor supermercadista. O estudo de caso feito na pesquisa foi no Centro de Distribuição desta rede supermercadista. O PRP consiste em determinar a menor rota a ser percorrida por um separador em um Centro de Distribuição (CD) de forma a coletar manualmente todos os produtos contidos em um determinado pedido. Tem-se como objetivo a aplicação de um modelo de Programação Linear Inteira Mista (PLIM), encontrado na literatura, e a comparação dos resultados obtidos com o atual método utilizado na empresa, a heurística SShape. Para isso, dados reais de pedidos de um determinado período foram coletados e algumas suposições relativas ao tamanho do problema e ao leiaute do CD foram feitas para gerar os 65 cenários de testes estabelecidos. Para atingir o objetivo almejado, foi necessário elaborar um algoritmo em três etapas, em linguagem de programação C#. A primeira etapa é o tratamento de dados e ajuste do leiaute para a elaboração do modelo Matemático. Com uso do solver GUROBI para a resolução dos testes, realizou-se a segunda etapa. A terceira etapa consistiu na aplicação da heurística S-Shape para possibilitar a comparação entre os métodos. As comparações entre o modelo aplicado e a heurística da empresa foram avaliadas em termos de economias (em metros) do trajeto gerado e tempo de resolução. Em 81,54% dos testes, o modelo obteve melhores resultados, gerando rotas com distâncias menores. Os outros 18,46% ambos os métodos retornaram o mesmo resultado. A melhoria média geral ficou em 8,41%. O modelo com parâmetro alterado resolveu 87,69% dos testes em até 30 minutos, considerado como tempo aceitável em termos práticos operacionais. Para os 12,31% dos testes resolvidos acima de 30 minutos, uma manipulação nos dados para contornar essa situação foi sugerida. Dessa forma, foi considerada como vantajosa a aplicação do modelo para o problema real de roteamento de pickers.Abstract: This work presents a real application of an exact model for the Picker Routing Problem (PRP), in a retail chain in the supermarket sector. The case study done in the research was in the Distribution Center of this supermarket chain. The PRP consists of determining the shortest route to be taken by a picker in a Distribution Center (DC) in order to manually collect all the products contained in a given order. The objective is to apply a Mixed Integer Linear Programming (MILP) model, found in the literature, and to compare the results obtained with the current method used in the company, the SShape heuristic. For this, actual order data for a given period was collected and some assumptions regarding the size of the problem and the CD layout were made to generate the 65 established test scenarios. To achieve the desired goal, it was necessary to develop an algorithm in three steps, in C # programming language. The first step is the data treatment and adjustment of the layout for the elaboration of the Mathematical model. Using the GUROBI solver to solve the tests, the second step was performed. The third step consisted of applying the S-Shape heuristic to make it possible to compare the methods. The comparisons between the applied model and the company's heuristic were evaluated in terms of savings (in meters) of the generated route and resolution time. In 81.54% of the tests, the model obtained better results, generating routes with shorter distances. The other 18.46% both methods returned the same result. The overall average improvement was 8.41%. The model with an altered parameter solved 87.69% of the tests within 30 minutes, considered an acceptable timeframe in operational practical terms. For the 12.31% of the tests resolved over 30 minutes, a manipulation of the data to get around this situation was suggested. Thus, it was considered advantageous to apply the model to the real problem of picker routing

Fuelling the zero-emissions road freight of the future: routing of mobile fuellers

The future of zero-emissions road freight is closely tied to the sufficient availability of new and clean fuel options such as electricity and Hydrogen. In goods distribution using Electric Commercial Vehicles (ECVs) and Hydrogen Fuel Cell Vehicles (HFCVs) a major challenge in the transition period would pertain to their limited autonomy and scarce and unevenly distributed refuelling stations. One viable solution to facilitate and speed up the adoption of ECVs/HFCVs by logistics, however, is to get the fuel to the point where it is needed (instead of diverting the route of delivery vehicles to refuelling stations) using "Mobile Fuellers (MFs)". These are mobile battery swapping/recharging vans or mobile Hydrogen fuellers that can travel to a running ECV/HFCV to provide the fuel they require to complete their delivery routes at a rendezvous time and space. In this presentation, new vehicle routing models will be presented for a third party company that provides MF services. In the proposed problem variant, the MF provider company receives routing plans of multiple customer companies and has to design routes for a fleet of capacitated MFs that have to synchronise their routes with the running vehicles to deliver the required amount of fuel on-the-fly. This presentation will discuss and compare several mathematical models based on different business models and collaborative logistics scenarios