20th January - 09:30 (Link: https://videoconf-colibri.zoom.us/j/87292833142) 

We describe a real life application of a container loading problem for a children’s shoes manufacturer. The children’s shoes ordered by each customer are packed into one or several large cardboard boxes, and these cardboard boxes are size customized for each set of shoe boxes to pack. Each cardboard box can pack different shoe sizes and models and it is to be delivered to one single customer. The goal is to pack the full order while minimizing the number of containers and, as the containers are not fixed size, also minimizing their volume. Mathematical programming plays a key role to improve the efficiency of packing shoes.

The European Commission regulation requires insurance companies to determine the maximum value of insured fire risk policies of all buildings that are partly or fully located within circle of a radius of 200 m. In this talk, we present the multi-start local search meta-heuristic that has been developed to solve the real case of an insurance company having more than 400 thousand insured buildings in mainland Portugal. A random sample of the data set was used and the solutions of the meta-heuristic were compared with the optimal solution of a MILP model based on the Maximal Covering Location Problem. The results show the proposed approach to be very efficient and effective in solving the problem.

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Manuel V.C. Vieira obtained his PhD from TU Delft, in The Netherlands. In his research, he has covered topics such as interior-point methods and satisfiability. More recently, he became interested in applying mathematical optimization to problems originating from industry, namely, layout problems and the container loading problem. He co-authored the book “Facility Layout: Mathematical Optimization Techniques and Engineering Applications”. He is currently Assistant Professor at Nova University of Lisbon, and member of the research centers CMA-UNL (Portugal) and GERAD (Canada).

Joana has a BSc in Mathematics and a MSc in Applied Mathematics: Actuarial, Statistics and Optimization fields both at the Faculdade de Ciências e Tecnologia. She also participated on an ERAMUS Programme at Universidad de Salamanca in Spain. In her thesis project, Joana used optimization algorithms and metaheuristics methods to solve an actuarial problem, whose goal was to evaluate the largest sum insured of all buildings that are partly or fully located within a radius of 200 meters. Indeed, the problem could be solved by exact methods, but the considering the dimensionality of the data, Joana turned her attention to the metaheuristics methods to overcame computational limitations. Regarding work experience, Joana was an assistant in a Graduate Training for Willis Towers Watson Create written and visual training materials used to guide the trainees and assist in the cases studies for the financial and actuarial mathematics and pensions funds themes and was part of a non-Life Actuarial Internship at Liberty Mutual Insurance. Joana joined KPMG for Forensic team in September 2017, where she currently occupies the position of Senior Advisor. Since Joana joined the Forensic team, she has participated in projects mainly associated with Financial Services and pharmaceutical companies, which are mainly related with Money Laundering and Terrorism Finance, Fraud and misconduct investigations, and Bribery and Corruption. Joana has international experience in Angola, Germany, Italy, United Kingdom, Netherlands, Panama, and Spain.