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
The principles and tools made available by the Industry 4.0, smart factories, or the Internet of Things (IoT), along with the adoption of more comprehensive simulation models, can significantly help the industry to face the current, huge external and internal challenges. This paper presents a new simulation-based approach to support decision making in the design and operational management of manufacturing systems. This approach is used to evaluate different layouts and resources allocation, and help managing operations, by integrating a simulation software with real-time data collected from the production assets through an IoT platform. The developed methodology uses a digital representation of the real production system (that may be viewed as a form of a digital twin) to assess different production scenarios. A set of key performance indicators (e.g. productivity) provided by the simulation can be used by the Manufacturing Execution System (MES) to generate production schedules. The developed approach was implemented and assessed in a real case study, showing its robustness and application potential. Its extension to other industrial contexts and sectors seems, therefore, quite promising. Copyright (C) 2021 The Authors.

Abstract
Omnichannel retailing and digitalization result in considerable challenges for the management and optimization of retail operations. The continued demand of quantitative insights, their practical need, and the growing availability of data motivates an increasing number of scientists and practitioners to intensify research on demand and supply-related issues in retailing. This featured cluster provides the state-of-the art literature on forecasting and digitalization technologies, channel structures and delivery concepts as well as logistics in omnichannel and online retailing. The featured cluster contains 17 articles that deal with such topics. © 2021 Elsevier B.V.

Abstract
The Real-Time Monitoring and Performance Management suite tool, known as UIL (User Interface Layer), was developed in the FASTEN project, a R&D initiative financed by the innovation and research program H2020 within a bilateral Europe-Brazil call. UIL was conceived and deployed in the IIoT architecture of the project. The goal was to provide a usercentered assistance to the human operator for both decision-responsibility and control loop, in a continuously updating information fashion, related to system's state. In order to have experimental results, a qualitative assessment was conducted in an industrial environment. The architecture proposed was based on the adoption of a Knowledge Engineering User Interface to support Operator 4.0. Our empirical experiments point out to a successful set of results. Copyright (C) 2021 The Authors.

Abstract
In their quest for sustainability, cities design and deploy smart mobility solutions aiming to improve the efficiency and management of transportation systems and to provide better services to citizens. Those solutions are often based on Information and Communication Technologies (ICT) and on digital services, but their maintenance and management are a greater challenge than their implementation. Problems can be difficult to identify since they can be exogenous or endogenous to the service provider. Usually, in their effort to maintain good service levels, companies implement complex and expensive information systems that use sensors to monitor infrastructure and hardware but ignore other sources of valuable information. In a digitalized world, customers easily report problems that are a cause of lower quality of service and worse user experience. However, for several reasons, service providers do not always pay due attention to these complaints. As communication channels are already open, we claim that customer participation through these reports can be used to significantly enhance the delivery and quality of mobility services. In this work we propose a methodology that takes advantage of customers’ participation in the maintenance and management of smart city solutions. With this methodology, we aim to redesign the process of customer interaction with service providers in order to improve the overall efficiency and the service experience. Our research is based on a case study from a public transport service in the metropolitan area of Porto, in Portugal. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Distribution warehouses are a critical part of supply chains, representing a nonnegligible share of the operating costs. This is especially true for unautomated, labor-intensive warehouses, partially due to time-consuming activities such as picking up items or traveling. Inventory categorization techniques, as well as zone storage assignment policies, may help in improving operations, but may also be short-sighted. This work presents a three-step methodology that uses probabilistic simulation, optimization, and event-based simulation (SOS) to analyze and experiment with layout and storage assignment policies to improve the picking performance. In the first stage, picking performance is estimated under different storage assignment policies and zone configurations using a probabilistic model. In the second stage, a mixed integer optimization model defines the overall warehouse layout by selecting the configuration and storage assignment policy for each zone. Finally, the optimized layout solution is tested under demand uncertainty in the third, final simulation phase, through a discrete-event simulation model. The SOS methodology was validated with three months of operational data from a large retailer's warehouse, successfully illustrating how it may be successfully used for improving the performance of a distribution warehouse.