Catarina Moreira Marques

Abstract
Effective warehouse management plays a pivotal role in optimizing supply chain performance, particularly in high-demand, time-sensitive environments. This study introduces a simulation-based decision support system designed to improve the management of Picking-By-Line (PBL) operations in cross-docking distribution centres. Developed in FlexSim and calibrated with empirical data from an industrial case study, the model replicates real-world warehouse conditions and is validated against observed operational performance. The tool supports warehouse managers in evaluating and comparing operational strategies, such as dynamic storage allocation policies and picker routing constraints, with the goal of reducing operator travel distances, mitigating congestion, and enhancing overall efficiency. A key contribution of this work is the integration of congestion-sensitive performance indicators that allow for a detailed analysis of the trade-offs between travel efficiency and localized congestion-an aspect often overlooked in traditional optimization methods. This study demonstrates the value of simulation as a scalable and realistic decision-support tool for optimizing PBL operations in complex and variable environments where human movement is a major cost and performance driver. The proposed tool bridges the gap between theoretical modelling and practical implementation, offering actionable insights for warehouse layout, space utilization, and resource allocation.

Abstract

Abstract
By connecting maritime and land transport, container terminals play a critical role in global logistics systems, as part of broader intermodal networks. The evolution of containerisation and technological advances, along with increased demand and volumes, led to significant adaptations in these terminals, as a way to improve productivity, reduce costs and increase competitiveness, while coping with spatial and operational constraints. For strategic decision-making, managing these complex systems can be enhanced by simulation models allowing the analysis of different scenarios in dynamic, uncertain environments. This work, presents a simulation-based decision support tool developed in the FlexSim software, to analyse different container terminal configurations, with a particular focus on automation and on sustainable practices to reduce the energy consumption of terminals. A discrete event simulation model was developed to study multiple scenarios impacting productivity, resource utilisation, and waiting times. The proposed approach allows the test and evaluation of management strategies for port operations, with preliminary results showing that sizing and planning of the fleets of automated guided vehicles (AGV) can significantly affect the total operating time, the energy consumed, and the costs associated with battery charging operations. Future research should explore additional factors affecting container terminal operations, such as the reorganisation of the storage area, while incorporating optimisation elements for work planning and resource allocation. Moreover, the simulation model will be tested and validated in a real case study, designed for the Port of Sines in Portugal. © 2024 The Authors.

Abstract
This research addresses the Frequency Setting Problem (FSP) together with vehicle technology selection for bus fleet sizing and management. A decision support tool was developed that combines a multi-criteria decision analysis, using the Analytic Hierarchy Process (AHP), and an enumeration procedure. The tool assists transportation operators in selecting optimal frequencies and vehicle technologies, considering economic, social, and environmental criteria. Computational experiments performed in the city of Niterói, Brazil, demonstrate the effectiveness of the tool. Scenarios with different criteria prioritizations highlight the flexibility of the approach and emphasize the need for a balance between all the sustainability dimensions. This approach positively impacts public transportation system performance, favouring higher-capacity vehicles while considering demand, and contributing to sustainable urban mobility. © 2024 The Authors.

Abstract