Cookies Policy
The website need some cookies and similar means to function. If you permit us, we will use those means to collect data on your visits for aggregated statistics to improve our service. Find out More
Accept Reject
  • Menu
About

About

Ana Viana holds a PhD in Electrical and Computers Engineering (University of Porto, 2004).

She is Head of the Centre for Industrial Engineering and Management of INESC TEC and Coordinator Professor at the Polytechnic of Porto, School of Engineering.

Her research interests focus on Combinatorial Optimisation, both on the development of exact and (meta-)heuristics approaches.

She led several research projects with public funding and publishes regularly in reference scientific journals of her area of activity.

Interest
Topics
Details

Details

013
Publications

2023

Stochastic crowd shipping last-mile delivery with correlated marginals and probabilistic constraints

Authors
Silva, M; Pedroso, JP; Viana, A;

Publication
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

Abstract

2023

Preface to the Special Issue on Operations Research in Healthcare

Authors
Viana, A; Marques, I; Dias, JM;

Publication
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH

Abstract

2023

A data-driven compensation scheme for last-mile delivery with crowdsourcing

Authors
Barbosa, M; Pedroso, JP; Viana, A;

Publication
COMPUTERS & OPERATIONS RESEARCH

Abstract

2023

Deep reinforcement learning for stochastic last-mile delivery with crowdshipping

Authors
Silva, M; Pedroso, JP; Viana, A;

Publication
EURO JOURNAL ON TRANSPORTATION AND LOGISTICS

Abstract

2022

The Probabilistic Travelling Salesman Problem with Crowdsourcing

Authors
Santini, A; Viana, A; Klimentova, X; Pedroso, JP;

Publication
COMPUTERS & OPERATIONS RESEARCH

Abstract
We study a variant of the Probabilistic Travelling Salesman Problem arising when retailers crowdsource last-mile deliveries to their own customers, who can refuse or accept in exchange for a reward. A planner must identify which deliveries to offer, knowing that all deliveries need fulfilment, either via crowdsourcing or using the retailer's own vehicle. We formalise the problem and position it in both the literature about crowdsourcing and among routing problems in which not all customers need a visit. We show that to evaluate the objective function of this stochastic problem for even one solution, one needs to solve an exponential number of Travelling Salesman Problems. To address this complexity, we propose Machine Learning and Monte Carlo simulation methods to approximate the objective function, and both a branch-and-bound algorithm and heuristics to reduce the number of evaluations. We show that these approaches work well on small size instances and derive managerial insights on the economic and environmental benefits of crowdsourcing to customers.

Supervised
thesis

2021

Production Planning and scheduling in the Footwear Industry

Author
CARLOS ANDRÉ VAZ MOREIRA

Institution
IPP-ISEP

2019

A data-driven compensation scheme for last-mile delivery with crowdsourcing

Author
Miguel Moreira da Silva Lima Barbosa

Institution
UP-FCUP

2018

ANÁLISE DA REDE LOGÍSTICA E POLÍTICAS DE APROVISIONAMENTO NUMA EMPRESA DE DISTRIBUIÇÃO DE CONTADORES ELÉTRICOS

Author
VÍTOR NETO MAGALHÃES

Institution
IPP-ISEP

2017

Otimização do posicionamento de PMUs numa rede elétrica

Author
TIAGO RAFAEL PINTO MONTEIRO

Institution
IPP-ISEP

2015

Desenvolvimento de Sequenciador para um Problema de Roteamento de Veículos

Author
HÉLDER FILIPE DE CASTRO PINHEIRO

Institution
IPP-ISEP