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About

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

  • Name

    Pedro Amorim
  • Role

    Research Coordinator
  • Since

    01st July 2013
012
Publications

2024

Synchronisation in vehicle routing: Classification schema, modelling framework and literature review

Authors
Soares, R; Marques, A; Amorim, P; Parragh, SN;

Publication
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

Abstract
The practical relevance and challenging nature of the Vehicle Routing Problem (VRP) have motivated the Operations Research community to consider different practical requirements and problem variants throughout the years. However, businesses still face increasingly specific and complex transportation re-quirements that need to be tackled, one of them being synchronisation. No literature contextualises syn-chronisation among other types of problem aspects of the VRP, increasing ambiguity in the nomenclature used by the community. The contributions of this paper originate from a literature review and are three-fold. First, new conceptual and classification schemas are proposed to analyse literature and re-organise different interdependencies that arise in routing decisions. Secondly, a modelling framework is presented based on the proposed schemas. Finally, an extensive literature review identifies future research gaps and opportunities in the field of VRPs with synchronisation.(c) 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )

2024

The drone-assisted vehicle routing problem with robot stations

Authors
Morim, A; Campuzano, G; Amorim, P; Mes, M; Lalla-Ruiz, E;

Publication
EXPERT SYSTEMS WITH APPLICATIONS

Abstract
Following the widespread interest of both the scientific community and companies in using autonomous vehicles to perform deliveries, we propose the 'Drone-Assisted Vehicle Routing Problem with Robot Stations' (VRPD-RS), a problem that combines two concepts studied in the autonomous vehicles literature: truck-drone tandems and robot stations. We model the VRPD-RS as a mixed-integer linear program (MILP) for two different objectives, the makespan and operational costs, and analyze the impact of adding trucks, drones, and robots to the delivery fleet. Given the computational complexity of the problem, we propose a General Variable Neighborhood Search (GVNS) metaheuristic to solve more realistic instances within reasonable computational times. Results show that, for small instances of 10 customers, where the solver obtains optimal solutions for almost all cases, the GVNS presents solutions with gaps of 0.7% to the solver for the makespan objective and gaps of 0.0% for the operational costs variant. For instances of up to 50 customers, the GVNS presents improvements of 21.5% for the makespan objective and 8.0% for the operational costs variant. Furthermore, we compare the GVNS with a Simulated Annealing (SA) metaheuristic, showing that the GVNS outperforms the SA for the whole set of instances and in more efficient computational times. Accordingly, the results highlight that including an additional drone in a truck-drone tandem increases delivery speed alongside a reduction in operational costs. Moreover, robot stations proved to be a useful delivery element as they were activated in almost every studied scenario.

2024

Learning efficient in-store picking strategies to reduce customer encounters in omnichannel retail

Authors
Neves-Moreira, F; Amorim, P;

Publication
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS

Abstract
Omnichannel retailers are reinventing stores to meet the growing demand of the online channel. Several retailers now use stores as supporting distribution centers to offer quicker Buy-Online-Pickup-In-Store (BOPS) and Ship-From-Store (SFS) services. They resort to in-store picking to serve online orders using existing assets. However, in-store picking operations require picker carts traveling through store aisles, competing for store space, and possibly harming the offline customer experience. To learn picking policies that acknowledge interactions between pickers and offline customers, we formalize a new problem called Dynamic In-store Picker Routing Problem (diPRP). This problem considers a picker that tries to pick online orders (seeking) while minimizing customer encounters (hiding) - preserving the offline customer experience. We model the problem as a Markov Decision Process (MDP) and solve it using a hybrid solution approach comprising mathematical programming and reinforcement learning components. Computational experiments on synthetic instances suggest that the algorithm converges to efficient policies. We apply our solution approach in the context of a large European retailer to assess the proposed policies regarding the number of orders picked and customers encountered. The learned policies are also tested in six different retail settings, demonstrating the flexibility of the proposed approach. Our work suggests that retailers should be able to scale the in-store picking of online orders without jeopardizing the experience of offline customers. The policies learned using the proposed solution approach reduced the number of customer encounters by up to 50%, compared to policies solely focused on picking orders. Thus, to pursue omnichannel strategies that adequately trade-off operational efficiency and customer experience, retailers cannot rely on actual simplistic picking strategies, such as choosing the shortest possible route.

2024

Customer Preferences for Delivery Service Attributes in Attended Home Delivery

Authors
Amorim, P; Dehoratius, N; Eng-Larsson, F; Martins, S;

Publication
MANAGEMENT SCIENCE

Abstract
Retailers face increasing competitive pressure to determine how best to deliver products purchased online to the end customer. Grocery retailers often require attended home delivery where the customer must be present to receive the delivery. For attended home delivery to function, the retailer and customer must agree on a delivery time slot that works for both parties. Using online data from a grocery retailer, we observe customer preferences for three delivery service attributes associated with each time slot: speed, precision, and timing. We define speed as the expected time between the placement of an order and its delivery, precision as the duration of the offered time slot, and timing as the availability of choices across times of the day and days of the week. We show that customers not only value speed as an attribute of delivery service but that precision and timing are also key drivers of the customer's time slot selection process. We also observe substantial customer heterogeneity in the willingness of customers to pay for time slots. Customers that differ in their loyalty to the retailer, basket value, basket size, and basket composition exhibit distinct differences in their willingness to pay. We show that retailers with the capability to tailor their time slot offerings to specific customer segments have the potential to generate approximately 9% more shipping revenue than those who cannot. Our findings inform practitioners seeking to design competitive fulfillment strategies and academics customer behavior in the attended home context.

2023

Minimizing Food Waste in Grocery Store Operations: Literature Review and Research Agenda

Authors
Riesenegger, L; Santos, MJ; Ostermeier, M; Martins, S; Amorim, P; Hübner, A;

Publication
Sustainability Analytics and Modeling

Abstract

Supervised
thesis

2022

Increasing the Dependability of Internet-of-Things Systems in the context of End-User Development Environments

Author
João Pedro Matos Teixeira Dias

Institution
UP-FEUP

2022

Exploring Arbitrage Opportunities For Increased Catalogue ROI In A Fashion E-Tailer

Author
Ana Margarida Machado Braga de Almendra

Institution
UP-FEUP

2022

Beyond a "Business as Usual" - Unraveling the Dynamics of Service Ecosystems through Service Platforms

Author
Nabila As'ad

Institution
UP-FEUP

2022

Self-explanatory computer-aided diagnosis with limited supervision

Author
Isabel Cristina Rio-Torto de Oliveira

Institution
UP-FEUP

2022

Specializing Risc-V Cores for Performance and Power

Author
Henrique Veloso de Sousa

Institution
UP-FEUP