Improving order-picking operations with precedence constraints through efficient storage location assignment: evidence from a retail company

This paper is inspired by a manual picking retail company where shape and weight constraints affect the order-picking process. We proposed an alternative clustering similarity index that considers the similarity, the weight and the shape of products. This similarity index was further incorporated in a storage allocation heuristic procedure to set the location of the products. We test the procedure in a retail company that supplies over 191 stores, in Northern Portugal. When comparing the strategy currently used in the company with this procedure, we found out that our approach enabled a reduction of up to 40% on the picking distance; a percentage of improvement that is 32% higher than the one achieved by applying the Jaccard index, a similarity index commonly used in the literature. This allows warehouses to save time and work faster.info:eu-repo/semantics/publishedVersio

New solution procedures for the order picker routing problem in U-shaped pick areas with a movable depot

This paper develops new solution procedures for the order picker routing problem in U-shaped order picking zones with a movable depot, which has so far only been solved using simple heuristics. The paper presents the frst exact solution approach, based on combinatorial Benders decomposition, as well as a heuristic approach based on dynamic programming that extends the idea of the venerable sweep algorithm. In a computational study, we demonstrate that the exact approach can solve small instances well, while the heuristic dynamic programming approach is fast and exhibits an average optimality gap close to zero in all test instances. Moreover, we investigate the infuence of various storage assignment policies from the literature and compare them to a newly derived policy that is shown to be advantageous under certain circumstances. Secondly, we investigate the efects of having a movable depot compared to a fxed one and the infuence of the efort to move the depot

Sequencing and Routing in a Large Warehouse with High Degree of Product Rotation

The paper deals with a sequencing and routing problem originated by a real-world application context. The problem consists in defining the best sequence of locations to visit within a warehouse for the storage and/or retrieval of a given set of items during a specified time horizon, where the storage/retrieval location of an item is given. Picking and put away of items are simultaneously addressed, by also considering some specific requirements given by the layout design and operating policies which are typical in the kind of warehouses under study. Specifically, the considered sequencing policy prescribes that storage locations must be replenished or emptied one at a time by following a specified order of precedence. Moreover, two fleet of vehicles are used to perform retrieving and storing operations, whose routing is restricted to disjoint areas of the warehouse. We model the problem as a constrained multicommodity flow problem on a space-time network, and we propose a Mixed-Integer Linear Programming formulation, whose primary goal is to minimize the time traveled by the vehicles during the time horizon. Since large-size realistic instances are hardly solvable within the time limit commonly imposed in the considered application context, a matheuristic approach based on a time horizon decomposition is proposed. Finally, we provide an extensive experimental analysis aiming at identifying suitable parameter settings for the proposed approach, and testing the matheuristic on particularly hard realistic scenarios. The computational experiments show the efficacy and the efficiency of the proposed approach

Diseño y evaluación de estrategias de picking en un almacén tipo plataforma de distribución

En este trabajo se evalúan alternativas en el proceso de picking de un almacén tipo plataforma de distribución. Tras un estudio de la bibliografía en este ámbito, se desarrollan los aspectos a evaluar. Se programa un modelo de simulación en el que evaluar las diferentes estrategías. EL almacén esta constituido por estanterías que albergan palets, y los pedidos pueden ser en forma de picking o de palets completos. Se miden diferentes KPI's para poder sacar resultados concluyentes. <br /

Picking process improvement: The case of a company in the sporting goods retail sector

Although, with Covid-19, some sports-related activities were temporarily affected, the pandemic reinforced the importance of physical activity for a healthy life, resulting in a greater practice of sports both formally and informally, which had already been gaining more and more adherence in Portugal. Having said this, companies in the sports-related activity sectors must be prepared for this reality. Markets are increasingly competitive, it is essential to revise and improve processes in a continuous and systematic way. Order picking is one of the processes that most requires this effort, as it is one of the processes that involves more working hours and has a direct impact on the quality and efficiency of the entire supply chain. This is clearly the case at the logistics centre of Company X, particularly in the area of bulky items. In this sense, this study focuses on finding appropriate strategies to improve this process. With this objective in mind, and based on the literature review, a Business Process Improvement (BPI) approach was used. As an integral part of this approach, and also as a consequence of the literature review, it was proposed an improvement solution that involves the replacement of the current pick-by-label method with pick-by-tablet combined with RFID technology as a confirmation method. All the analyses performed lead to the conclusion that this proposal may represent significant improvements in terms of process efficiency and effectiveness, thus meeting the objectives established for the project.Apesar de, com a Covid-19, algumas atividades ligadas ao desporto terem sido temporariamente afetadas, a pandemia veio reforçar a importância da atividade física para uma vida saudável, resultando numa maior prática de desporto tanto a nível formal como informal, que já vinham a ganhar cada vez mais adesão em Portugal. Dito isto, as empresas nos setores de atividades ligadas à prática desportiva devem estar preparadas para esta realidade. Os mercados são cada vez mais competitivos, é fundamental rever e melhorar os processos de uma forma contínua e sistemática. Order picking é um dos processos que mais exige este esforço, pois é um dos processos que implica mais horas de trabalho e tem um impacto direto na qualidade e eficiência de toda a cadeia de abastecimento. Este é claramente o caso no centro logístico da Empresa X, mais concretamente na área dos artigos volumosos. Neste sentido, o presente estudo foca-se em encontrar estratégias apropriadas que permitam melhorar este processo. Tendo em conta este objetivo, e com base na revisão de literatura, foi usada uma abordagem de Business Process Improvement (BPI). Como parte integrante desta abordagem, e também como consequência da revisão de literatura, foi proposta uma solução de melhoria que passa pela substituição do atual método de pick-by-label por pick-by-tablet juntamente com tecnologia RFID como método de confirmação. Todas as análises efetuadas permitem concluir que esta proposta poderá representar melhorias significativas no que diz respeito à eficiência e eficácia do processo, indo assim de encontro aos objetivos estabelecidos para o projeto

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

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

New solution approaches for optimization problems with combinatorial aspects in logistics management

This dissertation comprises five papers, which have been published in scientific journals between 2019 and 2022. The papers consider logistic optimization problems from three different subjects with a focus on intra-logistics. All considered optimization problems have strong combinatorial aspects. To solve the considered problems, various solution approaches including different decomposition techniques are employed. Paper 1 investigates the optimization of the layout and storage assignment in warehouses with U-shaped order picking zones. The paper considers two objectives, namely minimizing the order picker's walking distance and physical strain during order picking. To solve the problem, a semantic decomposition approach is proposed, which solves the problem in polynomial time. In a computational study, both considered objectives are found to be mostly complementary. Moreover, suggestions for advantageous layout designs and storage assignments are derived. Paper 2 considers the problem of how to stow bins on tow trains in order to minimize the handling personnel's physical strain for loading and unloading. The problem is shown to be NP-hard and decomposed semantically. Utilising the decomposition, the problem is solved exactly with dynamic programming and heuristically with a greedy randomized adaptive search procedure. A consecutive computational study shows that both procedures perform well. Beyond that, it investigates the influence of the tow train wagons' design on the considered objective. Paper 3 is concerned with the problem of scheduling jobs with time windows on unrelated parallel machines, which is a NP-hard optimization problem that has applications, i.a., in berth allocation and truck dock scheduling. The paper presents an exact logic-based Benders decomposition procedure and a heuristic solution approach based on a set partitioning formulation of the problem. Moreover, three distinct objectives, namely minimizing the makespan, the maximum flow time, and the maximum lateness are considered. Both procedures exhibit good performances in the concluding computational study. Paper 4 addresses the problem of order picker routing in a U-shaped order picking zone with the objective of minimizing the covered walking distance. The problem is proven to be NP-hard. An exact logic-based Benders decomposition procedure as well as a heuristic dynamic programming approach are developed and shown to perform well in computational tests. Beyond that, the paper discusses different storage assignment policies and compares them in a numeric study. Paper 5 studies scheduling electrically powered tow trains in in-plant production logistics. The problem is regarded as an Electric Vehicle Scheduling Problem, where tow trains must be assigned to timetabled service trips. Since the tow trains' range is limited, charging breaks need to be scheduled in-between trips, which require detours and time. The objective consists in minimizing the required fleet size. The problem is shown to be NP-hard. To solve the problem, Paper 5 proposes a branch-and-check approach that is applicable for various charging technologies, including battery swapping and plug-in charging with nonlinear charge increase. In a computational study, the approach's practical applicability is demonstrated. Moreover, influences of the batteries' maximum capacity and employed charging technology are investigated