Abstract
This study presents an assessment of the main research problems addressed in the literature on New Product Development (NPD) and its methodologies, for the pharmaceutical industry. The work is particularly focused on the establishment of an evolutionary perspective of the relevant modelling approaches, and on identifying the main current research challenges, considering the fast-changing business context of the industry. Main findings suggest a generalized misalignment of recent studies with today's technological and market trends, highlighting the need for new modelling strategies.

Abstract
This paper presents a new solution algorithm to solve the resource-constrained project scheduling problem with activity splitting and setup times. The option of splitting activities, known as activity preemption, has been studied in literature from various angles, and an overview of the main contributions will be given. The solution algorithm makes use of a meta-heuristic search for the resource-constrained project scheduling problem (RCPSP) using network transformations to split activities in subparts. More precisely, the project network is split up such that all possible preemptive parts are incorporated into an extended network as so-called activity segments, and setup times are incorporated between the different activity segments. Due to the inherent complexity to solve the problem for such huge project networks, a solution approach is proposed that selects the appropriate activity segments and ignores the remaining segments using a boolean satisfiability problem solver, and afterwards schedules these projects to near-optimality with the renewable resource constraints. The algorithm has been tested using a large computational experiment with five types of setup times. Moreover, an extension to the problem with overlaps between preemptive parts of activities has been proposed and it is shown that our algorithm can easily cope with this extension without changing it. Computational experiments show that activity preemption sometimes leads to makespan reductions without requiring a lot of splits in the activities. Moreover, is shown that the degree of these makespan reductions depends on the network and resource indicators of the project instance.

Abstract
Procurement plays an essential role in the supply of materials for the production of goods or products. The success of procurement management to fulfill demand with high service levels and on-time delivery relies on the suppliers' performance. Suppliers should be appropriately selected to source materials with the right quality, in the right quantity, at the right time, and for the right price. The scope of this problem, as well as other aspects such as the sourcing strategy, will depend on the type of items. Critical items, which represent high-profit impacts and high supply risks, should be approached comprehensively by considering all the main activities of the procurement process. This study focuses on a supplier selection problem integrated with inventory management under a multi-sourcing strategy, by taking into account stochastic demand and supply disruptions. This problem is approached by a simulation-optimization method, composed of discrete-event simulation and a genetic algorithm (GA). Finally, a numerical example is provided to illustrate the solution procedure.

Abstract
The search for logistics best-practices in international trade has led to the appearance of the Berth Allocation Problem. If the vessels have release dates, the problem is proved to be NP-hard and the performance of exact algorithms is not satisfactory, leading to the use of metaheuristics. This paper develops a Hybrid Evolutionary Algorithm for the discrete and dynamic Berth Allocation Problem. A challenge of using Genetic Algorithms is the identification of the best approach to model a specific problem. This paper proposes the use of frontier techniques (Data Envelopment Analysis and Free Disposal Hull models) to compare the performances of alternative specifications of the parameters for the algorithm proposed and to identify efficient solutions.

Abstract
The highly disruptive transformation that digital platforms are imposing on entire sectors of the economy, along with the broad digitalization of industrial business processes, is having an impact on supply chains around the world. To take advantage of this new aggregated market paradigm new business models with a heavy focus on servitization are changing the value proposition of businesses. In this paper, we describe a reference architectural framework designed to support a digital platform fostering the optimization of supply chains by the pairing of unused industrial capacity with production demand. This framework aims at harmonizing stakeholder requirements with specifications of different levels in order to set up a coherent reference blueprint that serves as a starting point for development activities. A four-layer approach is used to articulate between technical components, with the data and tools layers, and the ecosystem, with the business and interfaces layers. The overall architecture and component description is presented as extensions of the initial set of affordances.

Abstract
In this paper we present a Benders decomposition approach for the Berth Allocation Problem (BAP). Benders decomposition is a cutting plane method that has been widely used for solving large-scale mixed integer linear optimization problems. On the other hand, the Berth Allocation Problem is a NP-hard and large-scale problem that has been gaining relevance both from the practical and scientific points of view. In this work we address the discrete and dynamic version of the problem, and develop a new decomposition approach and apply it to a reformulation of the BAP based on the Heterogeneous Vehicle Routing Problem with Time Windows (HVRPTW) model. In a discrete and dynamic BAP each berth can moor one vessel at a time, and the vessels are not all available to moor at the beginning of the planning horizon (there is an availability time window). Computational tests are run to compare the proposed Benders Decomposition with a state-of-the-art commercial solver. © 2019, Springer Nature Switzerland AG.