Article
Engineering, Multidisciplinary
Tobias Hofmann, David Wenzel
Summary: The implementation of industrial robot systems in the automotive industry has significantly increased productivity, but has also introduced challenges such as technological complexity and safety issues. The goal is to develop algorithms and tools to optimize robot system scheduling.
OPTIMIZATION AND ENGINEERING
(2021)
Article
Computer Science, Interdisciplinary Applications
Christian Klanke, Sebastian Engell
Summary: This paper introduces a Simulation-Optimization approach that combines a tailored Evolutionary Algorithm with a high-fidelity simulation model to obtain optimized executable production schedules. The paper emphasizes the importance of batching decisions in improving the tardiness of production schedules and presents new crossover and mutation operators, as well as repair algorithms, for handling variable-length chromosomes. The results demonstrate the effectiveness of the approach in reducing tardiness and outperforming simpler approaches.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Automation & Control Systems
Alberto Faveto, Luigi Panza, Giulia Bruno, Vincenzo Cirimele, Saverio Stefano Furio, Franco Lombardi
Summary: Industrial companies are increasingly electrifying their equipment and processes as part of a broader energy transition. Energy efficiency and reducing environmental pollution in internal logistics are becoming competitive factors and research objectives. Wireless power transfer technology offers a contactless solution for reducing battery demand and vehicle downtimes. This study proposes a methodology for determining the optimal positioning of wireless charging units in warehouses, for both static and dynamic recharging. The approach uses a mathematical model and integer linear programming to find the best layout that meets energy requirements and minimizes costs. Testing the optimizer in different warehouse scenarios showed that integrated dynamic and static WPT systems can maintain a constant state of charge for electric vehicles during operation.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Green & Sustainable Science & Technology
Durdu Hakan Utku
Summary: This study proposes a new mathematical model to optimize production processes and increase customer satisfaction by minimizing production delays and preventing lost sales. The GAMS CPLEX 24.1.3 software is used to solve the mixed-integer programming problem related to minimizing production delays. Additionally, a simulation model is developed using ARENA simulation software to identify bottlenecks and improve production efficiency.
Article
Computer Science, Interdisciplinary Applications
Youness Frichi, Fouad Jawab, Lina Aboueljinane, Said Boutahari
Summary: This paper proposes new mathematical models for optimizing ambulance deployment and redeployment. The Q-MALP-M2 model performs better in terms of coverage and average waiting time compared to the Q-MALP-M1 model. The simulation-optimization results demonstrate that Q-MALP-M2 provides significantly improved results with shorter execution time compared to OptQuest.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Computer Science, Interdisciplinary Applications
J. E. Beasley
Summary: This paper addresses a practical problem in military mission planning, focusing on planning a path for robots to reach a target without being detected by enemy sensors. The robots can take actions to evade detection by knocking out or confusing sensors, with actions dependent on path and time.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Domenico Spensieri, Edvin Ablad, Robert Bohlin, Johan S. Carlson, Rikard Soderberg
Summary: The focus of the research is on modeling delays in robot coordination to optimize the overall cycle time of assembly lines. An efficient heuristic algorithm is proposed through modeling and optimizing the model.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2021)
Article
Engineering, Industrial
Jongsung Lee, Byung-In Kim, Mihee Nam
Summary: This paper presents a solution approach for the welding gantry robot scheduling problem in shipyards, which can effectively reduce the makespan according to experimental tests.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Construction & Building Technology
Tim M. Mueller, Marlene Sachs, Julius H. P. Breuer, Peter F. Pelz
Summary: The EU's climate targets are increasingly affecting the building sector, and energy-efficient and airtight buildings with effective ventilation systems are necessary to meet these targets. The planning of ventilation systems, including placement, wiring, and operation of fans, should consider partial load scenarios to reduce oversizing and increase energy efficiency. Mathematical optimization techniques can be used to control the complexity and support the design, leading to significant improvements in the efficiency of ventilation systems.
JOURNAL OF BUILDING ENGINEERING
(2023)
Article
Management
Hossein Mostafaei, Pedro M. Castro, Fabricio Oliveira, Iiro Harjunkoski
Summary: This paper introduces a mixed integer linear programming model for pipeline transportation scheduling, which considers factors such as interface material generation, planned shutdowns, and local market demands, resulting in better schedules. The use of generalized disjunctive programming and convex hull reformulation of disjunctions leads to stronger and more computationally efficient formulations for large-scale industrial cases.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Green & Sustainable Science & Technology
Yongjian Jiang, Dongyun Wang, Wenjun Xia, Wencai Li
Summary: In this study, a method for optimizing the electric motor assembly flowshop was proposed. By using discrete event simulation and Taguchi method, the optimization of logistics system configuration and AGV parameters was achieved, which resulted in improved efficiency and overall throughput of the system.
Article
Computer Science, Interdisciplinary Applications
Gustavo Cunha de Bittencourt, Rennan Danilo Seimetz Chagas, Victor Anselmo Silva, Igor Gira Peres Vianna, Rafael Pedro Longhi, Paulo Cesar Ribas, Virgilio Jose Martins Ferreira Filho
Summary: This study proposes a framework based on a mixed-integer programming model and a discrete-event simulator to address supply allocation and cost evaluation issues in deep-sea oil and gas exploration and production operations. The research evaluates different fleet management policies and compares the impacts of various cargo delivery strategies on operational efficiency.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Management
Muhammed Ordu, Eren Demir, Chris Tofallis, Murat M. Gunal
Summary: The healthcare system in the UK is under increasing pressure, necessitating the need to optimize existing resources without additional funding. Detailed modeling is required to analyze demand and capacity shortages across all specialties and services, providing decision support tools for key stakeholders to make rational and realistic plans.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2021)
Article
Management
L. A. Rhodes-Leader, B. L. Nelson, B. S. Onggo, D. J. Worthington
Summary: Disruption is a common problem in the airline industry, and this paper introduces a multi-fidelity modelling framework that combines deterministic integer programming with simulation optimization to tackle the Aircraft Recovery Problem. Empirical evaluation suggests that this combination consistently finds good rescheduling options.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2022)
Article
Computer Science, Artificial Intelligence
Hiva Malekpour, Ashkan Hafezalkotob, Kaveh Khalili-Damghani
Summary: Dynamic scheduling using real-time data in manufacturing systems allows for quick response to unforeseen events, reducing costs and making-span while enhancing customer satisfaction. The study focuses on a multi-product production system, considering competition and bargaining strategies among customers. A simulation-optimization approach based on discrete-event simulation and Simulated annealing is employed to minimize makespan in workstations, showing significant reductions for all players.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Management
Maria Meneses, Ines Marques, Ana Barbosa-Povoa
Summary: This study presents a new two-stage stochastic programming model for defining optimal ordering policies for blood products, taking into consideration the uncertainty in demand. The model is validated and shown to be applicable through a case study of a Portuguese hospital, and substantial reductions in wastage and costs are achieved by comparing different ordering policies.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Catia Barbosa, Carlos Malarranha, Americo Azevedo, Ana Carvalho, Ana Barbosa-Povoa
Summary: This article proposes a hybrid and hierarchical performance assessment model to evaluate the sustainability performance of make-to-order supply chains. By using different simulation methods, the model provides a comprehensive understanding of the sustainability aspect across the entire supply chain.
JOURNAL OF SIMULATION
(2023)
Article
Operations Research & Management Science
Joao Pires Ribeiro, Ana Paula F. D. Barbosa-Povoa
Summary: Supply Chain Management is constantly evolving, and Supply Chain Resilience (SCR) is a recent concept that has emerged from changes in business practices. However, there is still limited research on how to model and quantify SCR behavior. This study proposes a new resilient supply chain metric that is incorporated into an optimization model to maximize economic and responsiveness objectives. A case study is conducted to analyze the impacts perceived by downstream customers and to demonstrate the correlation between SC performance and the new SCR metric.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Diana Jorge, Antonio Pais Antunes, Tania Rodrigues Pereira Ramos, Ana Paula Barbosa-Povoa
Summary: This paper proposes a hybrid metaheuristic approach to solve the smart waste collection problem, utilizing lookahead heuristic and simulated annealing/neighborhood search algorithm to optimize collection schedules and routes. Results from both randomly-generated test instances and a real case study demonstrate the effectiveness and usefulness of this approach in practice.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Fabio Coelho, Rodrigo Macedo, Susana Relvas, Ana Barbosa-Povoa
Summary: This study investigates the improvement of in-house logistics operations in manufacturing companies through the development of a simulation model. The results show that the introduction of automated technologies, such as robots, can significantly enhance efficiency, while the proper planning of human resources is also crucial.
INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING
(2022)
Article
Engineering, Industrial
Carolina Soares de Morais, Diana Rita Ramos Jorge, Ana Raquel Aguiar, Ana Paula Barbosa-Povoa, Antonio Pais Antunes, Tania Rodrigues Pereira Ramos
Summary: This paper focuses on the Smart Waste Collection Routing Problem (SWCRP) with workload concerns and proposes a solution methodology to improve the efficiency of waste collection operations using real-time information and optimization algorithms.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE-OPERATIONS & LOGISTICS
(2023)
Editorial Material
Chemistry, Multidisciplinary
Antonio Paulo Moreira, Pedro Neto, Felix Vidal
APPLIED SCIENCES-BASEL
(2023)
Article
Economics
Paulo Abreu, Daniel Santos, Ana Barbosa-Povoa
Summary: Emergency medical services (EMS) are crucial in providing pre-hospital care. However, previous studies failed to fully address the need to characterize relevant contextual data and discuss the computational complexity of modern forecasting techniques in the EMS context. This study proposes a generic data-driven forecasting method that considers different demand patterns and the impact of neighboring zones on operational decisions. The method provides decision tools for predicting the dynamic demand of EMS and improving resource allocation.
SOCIO-ECONOMIC PLANNING SCIENCES
(2023)
Article
Automation & Control Systems
Diogo Fonseca, Mohammad Safeea, Pedro Neto
Summary: This article presents a novel mechanically flexible force and proximity hybrid sensor that is inexpensive and easy to apply on complex-shaped robot structures. The sensor's versatility, flexibility, thinness, accuracy, and repeatability were demonstrated through experimental trials. It was successfully applied in hand-guiding a robot and human-robot collision avoidance.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Automation & Control Systems
Pedro Matos, Pedro Neto
Summary: This paper presents the design and fabrication of a modular and low-cost 3D-printable robotic gripper that can grasp and hold different objects. It is a parallel gripper with a two-finger two-motor configuration, maximizing grasping force while maintaining compactness. The gripper structure includes three types of fingers: hard, flexible, and soft, and utilizes an embedded camera with computer vision processing for object recognition. Experimental tests show that it can grasp different objects with a maximum force of 76N per finger and millimeter-level positioning accuracy.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Computer Science, Interdisciplinary Applications
M. Safeea, P. Neto
Summary: Collaborative robots are rapidly growing and being used in various domains, working alongside humans in unstructured environments. Python and Simulink are essential tools for robot design and control algorithm development. This study introduces iiwaPy, a Python library, and SimulinkIIWA, for interfacing KUKA iiwa robots. Both interfaces support robot motion control and state monitoring, and provide open-source code and example applications.
INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING
(2023)
Article
Engineering, Industrial
Laura Duarte, Pedro Neto
Summary: This study proposes an action classification system using a Dynamic and Active-pixel Vision Sensor (DAVIS) to recognize primitive assembly tasks from human motion events data. Advanced deep learning and recurrent networks are utilized to classify spatial and temporal features. The proposed filters can remove about 65% of event data noise, achieving a high classification accuracy of up to 99.37% for trained subjects and 97.08% for new subjects.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Editorial Material
Robotics
Antonio Paulo Moreira, Pedro Neto, Felix Vidal
Article
Green & Sustainable Science & Technology
Joana Simoes, Tania Pinto-Varela, Margarida Gaspar de Matos, Ana Carvalho
Summary: Households are responsible for more than 50% of food waste in the European Union, but progress in reducing it has been slow. This study proposes a new conceptual model linking the amount of food waste with its causes to guide effective communication strategies. The results reveal correlations between motivations, behaviors, and the amount of food wasted. Tailored communication strategies are proposed based on different consumer types.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Computer Science, Artificial Intelligence
Bruno Barracosa, Joao Felicio, Ana Carvalho, Leonilde M. Moreira, Filipa Mendes, Sandra Cabo Verde, Ta nia Pinto-Varela
Summary: This work proposes a holistic decision support tool that integrates experimental data to aid diverse stakeholders and decision-makers in determining the most suitable testing strategies. The tool introduces a novel model for testing decisions in extreme situations and demonstrates its practical application using real experimental results. The results suggest that a decentralized testing strategy improves financial and time gains, while centralization allows for easier implementation and resource management with a slight performance loss.
DECISION SUPPORT SYSTEMS
(2023)
