Abstract
The chemical-pharmaceutical sector is facing an unprecedented fast-changing environment, with new market and technological trends impacting the companies' operational strategies. Managing the pharmaceutical supply chain (PSC) operations is, therefore, ever more complex and challenging. The goal of this work is to present a comprehensive overview of the current state of the industry and research developments; and then, to develop a new decision-making reference framework to assist in the creation of optimization-based decision support models. This will be achieved through a multi-perspective analysis that encompasses strategic and tactical planning decision-making, in the current and future business context of the chemical-pharmaceutical industry. The findings reveal a lack of research addressing the most prominent trends currently driving this sector, such as patient centricity or new technological developments, thus highlighting the disruptive nature of the expected changes in a highly conservative industry.

Abstract
Urban freight transport is an important enabling factor for economic growth and social activities in cities but despite its benefits, it also generates important negative externalities including traffic congestion, pollution, noise and overall less safety. Moreover, increased limitations on urban freight transport, including access constraints, limited kerbside and private parking spaces for loading/unloading, and the often prohibitive costs of installing logistics infrastructures in city centres, have further constrained urban freight transport. To address these issues, several city logistics solutions have been proposed, such as two-tier distribution systems and distribution systems based on mobile depots. In this paper, we focus on two-tier urban freight distribution systems based on mobile depots, where little or no physical infrastructure is considered and where storage is not permitted at transfer locations. In these types of systems, coordination and synchronisation between vehicles are essential, and the main objective is to have vehicles at the transfer locations in a need-to-be basis as a way of minimising the negative externalities. We review and analyse 13 cases found in the scientific literature, trial reports and online resources, and propose a classification of these systems based on the level of mobility and accessibility of transportation modes operating at the first-tier. Furthermore, we characterise the main components and operational features of the different systems, including the existence of multi-trips, the types of transport modes used at both tiers, transported loads and the organisation of the transfer sites (satellites). This work aims to contribute for a clearer characterisation of two-tier urban distribution systems based on mobile depots, to later support the development of the most adequate mathematical models and solution methods to be applied to each variant of this type of systems. © 2020 The Authors. Published by Elsevier B.V.

Abstract
Central areas of large cities offer in general many advantages to their inhabitants. Typically, a large number of products, services, and opportunities are available in those urban zones, thus increasing life quality. Unfortunately, these benefits are associated with increasing transportation activities that can cause serious problems, such as traffic congestion, excessive energy consumption, and pollution. This paper aims at presenting a new transport system that consists of transporting freight in long-haul passenger vehicles. Two mixed integer mathematical programming models are presented: one for total cost minimization and the other for the travel time minimization. The problem under study was considered as a multi-commodity network flow problem with time windows, multi transport-lines, and multiple vehicles. Three heuristics based on mixed integer programming (MIP) were designed to solve it: size reduction, LP-and-fix, and a combination of these two procedures. The proposed approaches were validated in a case study designed around the intercity passenger transport system, in Ceará, Northeast of Brazil. Several operational scenarios were evaluated, taking into account the available freight capacities. The developed MIP heuristics produced high-quality solutions, in reasonable computational times, with the LP-and-Fix algorithm outperforming the other approaches. © 2020 The Authors. Published by Elsevier B.V.

Abstract
The negative impacts of urban logistics have fostered the search for new distribution systems in inner city deliveries. In this context, interesting solutions can be developed around two-echelon distribution systems based on mobile depots (2E-MD), where loads arriving from the periphery of the city are directly transferred, at intermediate locations, from larger to smaller vehicles more suited to operate in the city centre. Four types of 2E-MD can be identified, according to the degree of mobility of larger vehicles and their accessibility to customers. In this paper, we propose a generic three-index arc-based mixed integer programming model, for a two-echelon vehicle routing problem, with synchronisation at the satellites and multi-trips at the second echelon. This generic base model is formulated for the most restrictive type of problems, where larger vehicles visit a a single transfer location and do not perform direct deliveries to customers, but it can be easily extended to address the other types of 2E-MD. The paper presents how these extensions account for the characteristics of the different types of 2E-MD. The generic model, its extensions and the impact of a set of valid inequalities are tested using problem instances adapted from the VRP literature. Results show that the proposed extensions do adequately address the specific features of the different types of 2E-MD, including multiple visits to satellites, and direct deliveries to customers. Nevertheless, the resulting models can only tackle rather small instances, even if the formulations can be strengthened by adding the valid inequalities proposed in the paper. © 2020 The Authors. Published by ELSEVIER B.V.

Abstract

Abstract
The potential of the Internet of Things (IoT) and other technologies in the realm of Industry 4.0 to generate valuable data for monitoring the performance of the production processes and the whole supply chain is well established. However, these large volumes of data can be used within planning and control systems (PCSs) to enhance real-time planning and decision-making. This paper conducts a literature review to envisage an overall system architecture that combines IoT and PCS for planning, monitoring and control of operations at the level of an industrial production process or at the level of its supply chain. Despite the extensive literature on IoT implementations, few studies explain the interactions between IoT and the components of PCS. It is expected that, with the increasing digitization of business processes, approaches with PCS and IoT become ubiquitous in the near future. © 2020, Springer Nature Switzerland AG.