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Sobre
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Sobre

Mestre e Doutor em Engenharia e Gestão Industrial pela FEUP.

Coordenador do Centro de Investigação em Engenharia e Gestão Industrial do INESC TEC Laboratório Associado.

Co-Fundador da LTPlabs - empresa de consultoria que aplica métodos analíticos avançados para ajudar a tomada de decisões complexas.

Especialista em planeamento da cadeia de abastecimento com ênfase em produtos alimentares. Foi Analista de Cadeia de Abastecimento na Total Raffinage Marketing (França). Investigador / Consultor em vários projetos relacionados a Gestão de Operações e suportados por diferentes tipos de entidades.

Autor de várias publicações em revistas internacionais na área da Investigação Operacional (por exemplo, Revista Internacional de Economia de Produção, Engenharia Industrial e Pesquisa de Química, Informática e Engenharia Química, Interfaces) - perfil de citação da Google.

Tópicos
de interesse
Detalhes

Detalhes

012
Publicações

2020

Cooperative coevolution of expressions for (r,Q) inventory management policies using genetic programming

Autores
Lopes, RL; Figueira, G; Amorim, P; Almada Lobo, B;

Publicação
International Journal of Production Research

Abstract
There are extensive studies in the literature about the reorder point/order quantity policies for inventory management, also known as (r,Q) policies. Over time different algorithms have been proposed to calculate the optimal parameters given the demand characteristics and a fixed cost structure, as well as several heuristics and meta-heuristics that calculate approximations with varying accuracy. This work proposes a new meta-heuristic that evolves closed-form expressions for both policy parameters simultaneously - Cooperative Coevolutionary Genetic Programming. The implementation used for the experimental work is verified with published results from the optimal algorithm, and a well-known hybrid heuristic. The evolved expressions are compared to those algorithms, and to the expressions of previous Genetic Programming approaches available in the literature. The results outperform the previous closed-form expressions and demonstrate competitiveness against numerical methods, reaching an optimality gap of less than (Formula presented.), while being two orders of magnitude faster. Moreover, the evolved expressions are compact, have good generalisation capabilities, and present an interesting structure resembling previous heuristics. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.

2020

Solving the grocery backroom sizing problem

Autores
Pires, M; Camanho, A; Amorim, P;

Publicação
International Journal of Production Research

Abstract
Backrooms are an important echelon of the retail supply chain. However, research focus has been mostly targeted to optimise both distribution centres and stores' sales area. In this paper, we propose two mathematical programming formulations to solve the grocery backroom sizing problem. This problem consists of determining the dimension of each storage department in the backroom area to optimise its overall efficiency. The first formulation is a bottom-up approach that aims to reduce the backroom life-cycle costs by determining the optimum floor space and storage height for each department. The second is a top-down approach based on Data Envelopment Analysis (DEA), which determines the efficient level of storage floor space for each backroom department, based on a comparison with the benchmarks observed among existing stores. Each approach has distinct characteristics that turn the models suitable for different retail contexts. We also describe the application of the proposed approaches to a case study of a European retailer. The application of this methodology in the design process demonstrated substantial potential for space savings (6% for the bottom-up model and 16% for the top-down model). This space reduction should either allow higher revenues in the sales area and/or lower backroom-related costs. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.

2020

Production scheduling in the context of Industry 4.0: review and trends

Autores
Parente, M; Figueira, G; Amorim, P; Marques, A;

Publicação
International Journal of Production Research

Abstract

2020

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

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

Publicação
Transportation Research Part E: Logistics and Transportation Review

Abstract

2020

Integrated planning of inbound and outbound logistics with a Rich Vehicle Routing Problem with Backhauls

Autores
Marques, A; Soares, R; Santos, MJ; Amorim, P;

Publicação
Omega

Abstract

Teses
supervisionadas

2019

Towards solving a robust and sustainable Vehicle Routing Problem with Backhauls

Autor
Maria João Martins dos Santos

Instituição
UP-FEUP

2019

Supply Chain Modelling and Supplier Selection under Supply Chain Risk Management in the Aerospace Industry

Autor
Nuno Bernardo Gonçalves Falcão e Cunha

Instituição
UP-FEUP

2019

Improving Value Creation in Technical Industries: an Operations Management Perspective

Autor
Ana Catarina Pires Pinto

Instituição
UP-FEUP

2019

A Sustainable and Optimized Biofuel Supply Chain for Portugal Mainland

Autor
Alda Almendra Henriques

Instituição
UP-FEUP

2019

Delivery Time Slot Management Methods in Online Retail

Autor
Armando Silvestre Loureiro Peixoto

Instituição
UP-FEUP