Dean of Engineering Office
Engineering 7 (E7), Room 7302
Direct line: 519-888-4885
Internal line: ext. 44885
Professor, Department of Industrial Engineering
University of Porto
Cutting and Packing problems are hard combinatorial optimization problems that arise in the context of several manufacturing and process industries or in their supply chains. These problems occur whenever a bigger object or space has to be divided into smaller objects or spaces, so that waste is minimized. This is the case when cutting paper rolls in the paper industry, large wood boards into smaller rectangular panels in the furniture industry, irregularly shaped garment parts from fabric rolls in the apparel industry, but also the case when packing boxes on pallets and these inside trucks or containers, in logistics applications. All these problems have in common the existence of a geometric sub-problem, which deals with the small object non-overlap constraints.
The resolution of these problems is not only a scientific challenge, given its intrinsic difficulty, but has also a great economic impact as it contributes to the decrease of one of the major cost factors for many production sectors: the raw-materials. In some industries raw-material may represent up to 40% of the total production costs. It has also a significant environmental repercussion as it leads to a less intense exploration of the natural resources from where the raw-materials are extracted, and decreases the quantity of garbage generated, which frequently has also important environmental impacts. In logistics applications, minimizing container and truck loading space waste directly leads to less transportation needs and therefore to smaller logistics costs and less pollution.
In this talk the several Cutting and Packing problems will be characterized and exemplified, based on Gerhard Wäscher’s typology (2007), allowing non-specialists to have a broad view over the area. Afterwards, as geometry plays a critical role in these problems, the geometric manipulation techniques more relevant for Cutting and Packing problems resolution will be presented. Finally, aiming to illustrate some of the most recent developments in the area, some approaches based on heuristics and metaheuristics, for the container loading problem, and based on mathematical programming models, for the irregular packing problem, will be described.
Dr. Oliveira’s main area of scientific activity is Operations Research and Management Science. Within Operations Research his main application area are the Cutting and Packing Problems, while from the techniques viewpoint his research is centered in the use and development of Metaheuristics approaches and their hybridization with Mathematical Programming based methods.
Cutting and Packing problems are hard combinatorial optimization problems that arise under several practical contexts, whenever big pieces of raw-material have to be cut into smaller items, or small items have to be packed inside a larger container, so that waste is minimized. These problems include hard geometric constraints when dealing with the optimization layer.
Dr. Oliveira has also worked on Vehicle Routing Problem, especially in the integration of route definition with the container loading problem. His research on Lotsizing and Scheduling problems in industrial contexts mainly builds on his expertise on Metaheuristics and optimization.
Dr. Oliveira has been giving special attention in the last years to several problems arising in the Transportation sector, in particular freight transportation. Therefore, new frameworks to assess and enforce cargo stability, both static and dynamic, weight distribution and other relevant goals in road transportation, have been developed, implemented and tested. Another important line of research is related to the car rental industry, where integration of pricing and capacity planning decisions has been approached, under a revenue management framework.
Dr. Oliveira has also worked on the use of the quantitative methods, provided by Operations Research and Management Science, to support decision making in Higher Education institutions management, which includes workload models, sustainability, institutional benchmarking and assessment and evaluation of institutions and teaching staff.
*Light refreshments will be served at 12 noon