O IO2021 - XXI Congresso da Associação Portuguesa de Investigação Operacional realizar-se-á em modo exclusivamente presencial no hotel Eurostars da Figueira da Foz, de 7 a 8 de novembro de 2021.
Como é habitual, podem ser submetidos resumos (em português ou inglês) e, pós-congresso, artigos completos (neste último caso, em língua inglesa). Os artigos completos que forem aceites no processo de revisão serão publicados nos Springer Proceedings in Mathematics & Statistics.
Manufacturing systems are achieving unprecedented levels of complexity, which arises from the need to manage a significant set of conflicting objectives. Simulation is a powerful method that can provide significant levels of detail and flexibility in modelling systems. The challenge is to develop new simulation-based models to study complex manufacturing systems.
The pharmaceutical industry is being challenged to become more cost-efficient and responsive when developing and making drugs. Scientific and technological breakthroughs, increasing societal pressures, stringent regulations, and fast-changing markets are pushing the pharmaceutical supply chain to the limit. The challenge is to develop mathematical models to design and run large pharmaceutical chains.
The manufacturing industry strives for tools that are capable of quantifying, demonstrating, and finding the sweet spot of running the processes, production lines, plants, and supply chains. The immediate objective is to smooth out the running systems as much as possible, even when the systems are running under severe conditions. Although this goal appears to be contradictory, emerging manufacturing paradigms, as is the Industry 4.0, support the development and application of tools focused on improving output and quality and reducing downtimes. While this path is generally well seen, there is still work to do to estimate the extension of such benefits in the existing systems. To accomplish this, data-driven methods, such as simulation, take advantage of data to learn how to make the best decisions.
The objetive was to design a dynamic buffering and inventory system based on DDMRP methodology [Video]
The main objective was to suggest solutions to achieve a profitable and sustainable operation of the Simio's BBQ Smoke Pit restaurant [Video]
The goal was to propose recommendations for optimizing waving and picking strategies in warehouse management [Video]
The challenge was to optimize the operations of an airport by studying and evaluating alternative processes and technologies from the passenger arrivals to the terminal areas [Video]
EUREKATHON is a data-driven competition that addresses societal issues associated with sustainable development goals
A two-level optimisation-simulation method for production planning and scheduling: the industrial case of a human–robot collaborative assembly line
Vieira M., Moniz S., Gonçalves B., Pinto-Varela T., Barbosa-Póvoa A., & Neto P.
Thirty Years of Flexible Job-Shop Scheduling: A Bibliometric Study
Coelho P., Pinto A., Moniz S., & Silva C.
Hybrid optimisation approach for sequencing and assignment decision-making in reconfigurable assembly lines
Maganha, I., Silva, C., Klement, N., dit Eynaud, A. B., Durville, L., & Moniz, S.
Optimal design of additive manufacturing supply chains
Basto, J., Ferreira, J. S., Alcalá, S. G., Frazzon, E., & Moniz, S.
A simulation approach for spare parts supply chain management
Caldas, N., Pinho de Sousa, J., Alcalá, S. G., Frazzon, E., & Moniz, S.
Integrating Simulation and Optimization for Process Planning and Scheduling Problems
Vieira, M., Moniz, S., Gonçalves, B., Pinto-Varela, T., & Barbosa-Póvoa, A. P.
Challenges in Decision-Making Modelling for New Product Development in the Pharmaceutical Industry. Computer Aided Chemical Engineering
Marques, C. M., Moniz, S., & Pinho de Sousa, J.
Strategic decision-making in the pharmaceutical industry: A unified decision-making framework
Marques, C. M., Moniz, S., & Pinho de Sousa, J.
Simulation-Optimization Approach for the Decision-Support on the Planning and Scheduling of Automated Assembly Lines
Vieira, M., Barbosa-Póvoa, A. P., Moniz, S., & Pinto-Varela, T.
A simulation-optimization approach to integrate process design and planning decisions under technical and market uncertainties: A case from the chemical-pharmaceutical industry
Vieira, M., Pinto-Varela, T., Barbosa-Póvoa, A. P., & Moniz, S.
Optimal planning and campaign scheduling of biopharmaceutical processes using a continuous-time formulation
Vieira, M., Pinto-Varela, T., Moniz, S., Barbosa-Póvoa, A. P., & Papageorgiou, L. G.
Optimization and Monte Carlo Simulation for Product Launch Planning under Uncertainty
Marques, C. M., Moniz, S., Pinho de Sousa, J., & Barbosa-Póvoa, A. P.
Recent Trends and Challenges in Planning and Scheduling of Chemical-Pharmaceutical Plants
Moniz, S., Barbosa-Póvoa, A. P., & Pinho de Sousa, J.
On the complexity of production planning and scheduling in the pharmaceutical industry: the Delivery Trade-offs Matrix
Moniz, S., Barbosa Póvoa, A. P., & Pinho de Sousa, J.
Solution Methodology for Scheduling Problems in Batch Plants
Moniz, S., Barbosa-Póvoa, A. P., Pinho de Sousa, J., & Duarte, P.
Simultaneous regular and non-regular production scheduling of multipurpose batch plants: A real chemical–pharmaceutical case study
Moniz, S., Barbosa Póvoa, A. P., & Pinho de Sousa, J.
New General Discrete-Time Scheduling Model for Multipurpose Batch Plants
Moniz, S., Barbosa Póvoa, A. P., & Pinho de Sousa, J.
Scheduling with equipment redesign in multipurpose batch plants
Moniz, S., Barbosa-Póvoa, A. P., & Pinho de Sousa, J.
Regular and non-regular production scheduling of multipurpose batch plants
Moniz, S., Barbosa-Póvoa, A. P., & Pinho de Sousa, J.
FuturePharma - The FuturePharma project goal is to develop optimization models with practical use for boosting the integration of complex decisions that occur at different levels of the pharmaceutical supply chain | FCT | Budget: 249.361,87 euros | Partners: Universidade de Coimbra, INESC TEC, and Instituto Superior Técnico
PRODUTECH4S&C - New methodologies and tools to develop new products, services, and innovative production technologies, aligned with the circular economy's challenges. | P2020 | Partners: 23 partners, among which Universidade de Coimbra
3DProductionChains - Introducing 3D Printing into the Production Chain: Modeling the Effects and Providing Guidance Using Data Analysis and Advanced Modeling | MIT Seed Projects | Partners: Universidade de Coimbra and MIT
PENELOPE - Pilot lines for large-part high-precision manufacturing proposes a novel methodology linking product-centric data management and production planning and scheduling in a closed-loop digital pipeline for ensuring an accurate and precise manufacturability from the initial product design | H2020 | Budget: 20.818.478,25 euros | Partners: 31 partners, among which Universidade de Coimbra
DM4Manufacturing Aligning Manufacturing Decision Making with Advanced Manufacturing Technologies | PORTUGAL 2020 | Budget: 1.677.691,31 euros | Partners: Universidade de Coimbra, INESC TEC, and Instituto Superior Técnico
Introduces simulation methods with a focus on modeling and analysis of real-world problems. Covers queuing models, probability and statistics in simulation, conceptual modeling, verification and validation of simulation models, and process design and analysis. Applications to manufacturing, logistics, transportation, and services will be discussed. It includes a team project to solve a large-scale simulation problem of practical interest.
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Addresses the theory and practice of production management as a functional area of the operations. Covers process design and analysis, production line balancing, design of factory layouts, forecasting methods, inventory models, production planning and scheduling, concepts of supply chains, and key lean manufacturing tools. It includes a team project to solve a problem of practical interest.
For those interested in more information on Production Management please click here
Aims at equipping students with knowledge and communication skills, and focuses on learning the strategic and tactical use of data to conduct decision-making processes. This curricular unit seeks to increase communication skills and use data tools through practice and real-world examples. Emphasis will be placed on the communication of quantitative information as well as the improvement of data storytelling skills.
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New approaches for simulation will leverage best practices to engineer factories and production processes at the earlier stages of their development. This can be done by using several models to investigate a broad spectrum of complex issues.
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In the pharmaceutical industry, the ability to bring new drugs into the market consistently is a central issue to remain competitive and maintain economic sustainability. Several challenges arise during this phase.
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Major technological advances are changing the way pharma companies operate and manage their operations. These companies are continually being challenged to become ever more cost-efficient and responsive to the delivery of drugs.