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About

Master of Science and Doctor of Philosophy in Industrial Engineering and Management by FEUP.

Head of the Research Center for Industrial Engineering and Management from INESC TEC Laboratório Associado.

Assistant Professor at the Department of Industrial Engineering and Management at FEUP.

Co Founder of LTPlabs - consultancy company that applies advanced analytical methods to help make better complex decisions.

Specialist in supply chain planning with an emphasis on food products. He was Supply Chain Analyst at Total Raffinage Marketing (França). Researcher/Consultant in several projects related to Operations Management and supported by different types of entities.

Author of several publications in international journals in the field of Operations Research (for example, International Journal of Production Economics, Industrial Engineering and Chemistry Research, Computers and Chemical Engineering, Interfaces) - Google citation profile.

Interest
Topics
Details

Details

014
Publications

2021

A bilevel approach for the collaborative transportation planning problem

Authors
Santos, MJ; Curcio, E; Amorim, P; Carvalho, M; Marques, A;

Publication
International Journal of Production Economics

Abstract
The integration of the outbound and the inbound logistics of a company leads to a large transportation network, allowing to detect backhauling opportunities to increase the efficiency of the transportation. In collaborative networks, backhauling is used to find profitable services in the return trip to the depot and to reduce empty running of vehicles. This work investigates the vertical collaboration between a shipper and a carrier for the planning of integrated inbound and outbound transportation. Based on the hierarchical nature of the relation between the shipper and the carrier and their different goals, the problem is formulated as a bilevel Vehicle Routing Problem with Selective Backhauls (VRPSB). At the upper level, the shipper decides the minimum cost delivery routes and the set of incentives offered to the carrier to perform integrated routes. At the lower level, the carrier decides which incentives are accepted and on which routes the backhaul customers are visited. We devise a mathematical programming formulation for the bilevel VRPSB, where the routing and the pricing problems are optimized simultaneously, and propose an equivalent reformulation to reduce the problem to a single-level VRPSB. The impact of collaboration is evaluated against non-collaborative approaches and two different side payment schemes. The results suggest that our bilevel approach leads to solutions with higher synergy values than the approaches with side payments. © 2020 Elsevier B.V.

2021

A green lateral collaborative problem under different transportation strategies and profit allocation methods

Authors
Joa, M; Martins, S; Amorim, P; Almada Lobo, B;

Publication
JOURNAL OF CLEANER PRODUCTION

Abstract
Collaboration between companies in transportation problems seeks to reduce empty running of vehicles and to increase the use of vehicles' capacity. Motivated by a case study in the food supply chain, this paper examines a lateral collaboration between a leading retailer (LR), a third party logistics provider (3 PL) and different producers. Three collaborative strategies may be implemented simultaneously, namely pickup-delivery, collection and cross-docking. The collaborative pickup-delivery allows an entity to serve customers of another in the backhaul trips of the vehicles. The collaborative collection allows loads to be picked up at the producers in the backhauling routes of the LR and the 3 PL, instead of the traditional outsourcing. The collaborative cross-docking allows the producers to cross-dock their cargo at the depot of another entity, which is then consolidated and shipped with other loads, either in linehaul or backhaul routes. The collaborative problem is formulated with three different objective functions: minimizing total operational costs, minimizing total fuel consumption and minimizing operational and CO2 emissions costs. The synergy value of collaborative solutions is assessed in terms of costs and environmental impact. Three proportional allocation methods from the literature are used to distribute the collaborative gains among the entities, and their limitations and capabilities to attend fairness criteria are analyzed. Collaboration is able to reduce the global fuel consumption in 26% and the global operational costs in 28%, independently of the objective function used to model the problem. The collaborative pickup-delivery strategy outperforms the other two in the majority of instances under different objectives and parameter settings. The collaborative collection is favoured when the ordering loads from producers increase. The collaborative cross-docking tends to be implemented when the producers are located close to the depot of the 3 PL.

2021

Solving the grocery backroom layout problem

Authors
Pires, M; Silva, E; Amorim, P;

Publication
International Journal of Production Research

Abstract

2020

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

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

Publication
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

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

Publication
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.

Supervised
thesis

2020

New models and methods for the Vehicle Routing Problem with Multiple Synchronisation Constraints

Author
Ricardo Filipe Ferreira Soares

Institution
UP-FEUP

2020

Otimização da Cadeia de Transportes

Author
Ana Cristina Oliveira Gomes

Institution
UP-FEP

2020

A Sustainable and Optimized Biofuel Supply Chain for Portugal Mainland

Author
Alda Almendra Henriques

Institution
UP-FEUP

2020

Flexibilidade no desenho das cadeias de abastecimento

Author
Luís Filipe Rodrigues Prado

Institution
UP-FEUP

2020

General Variable Neighborhood Search for the Drone-Assisted Vehicle Routing Problem with Robot Stations

Author
André Craveiro Morim

Institution
UP-FEUP