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009
Publications

2022

Fostering Customer Bargaining and E-Procurement Through a Decentralised Marketplace on the Blockchain

Authors
Martins, J; Parente, M; Amorim Lopes, M; Amaral, L; Figueira, G; Rocha, P; Amorim, P;

Publication
IEEE Transactions on Engineering Management

Abstract

2021

Improving picking performance at a large retailer warehouse by combining probabilistic simulation, optimization, and discrete-event simulation

Authors
Amorim Lopes, M; Guimaraes, L; Alves, J; Almada Lobo, B;

Publication
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH

Abstract
Distribution warehouses are a critical part of supply chains, representing a nonnegligible share of the operating costs. This is especially true for unautomated, labor-intensive warehouses, partially due to time-consuming activities such as picking up items or traveling. Inventory categorization techniques, as well as zone storage assignment policies, may help in improving operations, but may also be short-sighted. This work presents a three-step methodology that uses probabilistic simulation, optimization, and event-based simulation (SOS) to analyze and experiment with layout and storage assignment policies to improve the picking performance. In the first stage, picking performance is estimated under different storage assignment policies and zone configurations using a probabilistic model. In the second stage, a mixed integer optimization model defines the overall warehouse layout by selecting the configuration and storage assignment policy for each zone. Finally, the optimized layout solution is tested under demand uncertainty in the third, final simulation phase, through a discrete-event simulation model. The SOS methodology was validated with three months of operational data from a large retailer's warehouse, successfully illustrating how it may be successfully used for improving the performance of a distribution warehouse.

2021

Enhancing optimization planning models for health human resources management with foresight

Authors
Amorim Lopes, M; Oliveira, M; Raposo, M; Cardoso Grilo, T; Alvarenga, A; Barbas, M; Alves, M; Vieira, A; Barbosa Povoa, A;

Publication
Omega (United Kingdom)

Abstract
Achieving a balanced healthcare workforce requires health planners to adjust the supply of health human resources (HHR). Mathematical programming models have been widely used to assist such planning, but the way uncertainty is usually considered in these models entails methodological and practical issues and often disregards radical yet plausible changes to the future. This study proposes a new socio-technical methodology to factor in uncertainty over the future within mathematical programming modelling. The methodological approach makes use of foresight and scenario planning concepts to build tailor-made scenarios and scenario fit input parameters, which are then used within mathematical programming models. Health stakeholders and experts are engaged in the scenario building process. Causal map modelling and morphological analysis are adopted to digest stakeholders and experts’ information about the future and give origin to contrasting and meaningful scenarios describing plausible future. These scenarios are then adjusted and validated by stakeholders and experts, who then elicit their best quantitative estimates for coherent combinations of input parameters for the mathematical programming model under each scenario. These sets of parameters for each scenario are then fed to the mathematical programming model to obtain optimal solutions that can be interpreted in light of the meaning of the scenario. The proposed methodology has been applied to a case study involving HHR planning in Portugal, but its scope far extends HHR planning, being especially suited for addressing strategic and policy planning problems that are sensitive to input parameters. © 2020

2020

The multi-period vehicle routing problem with refueling decisions: Traveling further to decrease fuel cost?

Authors
Neves Moreira, F; Amorim Lopes, M; Amorim, P;

Publication
Transportation Research Part E: Logistics and Transportation Review

Abstract

2020

Systems, economics, and neoliberal politics: Theories to understand missed nursing care

Authors
Jones, T; Drach Zahavy, A; Amorim Lopes, M; Willis, E;

Publication
Nursing and Health Sciences

Abstract
The phenomenon of missed nursing care is endemic across all sectors. Nurse leaders have drawn attention to the implications of missed care for patient outcomes, with calls to develop clear political, methodological, and theoretical approaches. As part of this call, we describe three structural theories that inform frameworks of missed care: systems theory, economic theory, and neoliberal politics. The final section provides commentary on the strengths and limitations of these three theories, in the light of structuration theory and calls to balance this research agenda by reinstating nurse agency and examining the interactions between nurses as agents and the health systems as structures. The paper argues that a better understanding of variations in structure–agency interaction across the healthcare system might lead to more effective interventions at strategic leverage points. © 2020 John Wiley & Sons Australia, Ltd

Supervised
thesis

2021

Proposta de um método de avaliação da sustentabilidade de um produto para venda num mercado online, aplicando método multicritério

Author
Alexandra Sofia Ferreira de Oliveira

Institution
UP-FEUP

2021

Willingness to pay for green premiums through a sustainable marketplace

Author
Francisco Armando Teixeira Ferreira

Institution
UP-FEUP

2021

An Ethereum-based point of sale system for retail stores

Author
Maria Betânia Benita Afonso

Institution
UP-FEUP

2021

Using Machine Learning to classify HS codes for Fashion Products

Author
Ivânia Maria Afonso Barbosa

Institution
UP-FEUP

2021

Análise e Melhoria do Processo de Distribuição do Circuito do Medicamento na Farmácia Hospitalar

Author
Ana Rita Almeida Rodrigues

Institution
UP-FEUP