Rosário Moreira

Abstract
The retail industry is becoming increasingly competitive; as a result, companies are seeking to reduce inefficiencies in their supply chains. One way of increasing the efficiency of operations inside a warehouse is by better allocating products in the available spaces. In this paper, we propose a new heuristic approach to solving the storage location assignment problem (SLAP) considering precedence constraints, in multi-aisle, multi-product picking warehouses. A two-phase heuristic procedure is developed: the products are clustered and assigned to the available spaces. We tested the procedure in the non-perishables warehouse of a real-world Portuguese retail chain, which supplies 191 stores per day. The results show that the new assignment of products allows for an improvement of up to 15% on the distance travelled by the pickers, which implies savings of approximately 477 km per month. This problem is a special case of SLAP since we are dealing with large percentages of non-uniform products. This procedure incorporates four relevant criteria for the allocation decision: the products' similarity, demand and weight, and the distance travelled by the picker. By using a two-phase heuristic method, this study offers companies and academics an alternative and more effective solution for SLAP than the usual methods based on the creation of density zones.

Abstract

Abstract
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.

Abstract
This research establishes a comprehensive chronological and geographical overview of the recent topics mostly debated about the use of Lean thinking in services, disclosing its main trends, gaps and weaknesses. An ample compilation of research from Web of Science and Scopus was examined, and bibliometric analyses were performed, namely publication counting, and abstract, co-citation and co-word analysis. Unfolding Lean implementation projects and evaluating its outcomes are the most frequent themes. Reducing waste and increasing efficiency are often mentioned as the benefits. There are clear gaps in research density between multiple service sectors and healthcare; lack of established models and extensive use of case study method are the weaknesses of the studies in this field. This paper allows Lean practitioners having a sketch of the landscape of this field and its trends. This is the first effort to synthesize those topics in service industry as a whole, using bibliometric methods.

Abstract
A zero-one quadratic assignment model has been proposed for dealing with the storage location assignment problem when there are weight constraints. Our analysis shows that operations can be improved using our model. When comparing the strategy currently used in a real-life company with the designed model, we found that the new placement of products allowed a reduction of up to 22% on the picking distance. This saving is higher than that achieved with the creation of density zones, a procedure commonly used to deal with weight constraints, according to the literature.