Maria Antónia Carravilla
University of Porto
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Publication
Featured researches published by Maria Antónia Carravilla.
International Journal of Production Research | 2007
Bernardo Almada-Lobo; Diego Klabjan; Maria Antónia Carravilla; José Fernando Oliveira
In production planning in the glass container industry, machine-dependent setup times and costs are incurred for switch overs from one product to another. The resulting multi-item capacitated lot-sizing problem has sequence-dependent setup times and costs. We present two novel linear mixed-integer programming formulations for this problem, incorporating all the necessary features of setup carryovers. The compact formulation has polynomially many constraints, whereas the stronger formulation uses an exponential number of constraints that can be separated in polynomial time. We also present a five-step heuristic that is effective both in finding a feasible solution (even for tightly capacitated instances) and in producing good solutions to these problems. We report computational experiments.
European Journal of Operational Research | 1995
Maria Antónia Carravilla; Jorge Pinho de Sousa
In this paper, we analyse a complex production planning problem in a Make-To-Order company, involving quoting due dates, along with production scheduling, some plant layout decisions and line balancing issues. A general framework has been developed that identifies the main levels for decision making, and tackles these problems in a hierarchical fashion, the resulting interactions being carefully taken into consideration. This framework, based on considering discretised planning horizons, is implemented on a Decision Support System developed around an interface specially designed to involve the various participants in the planning process. In practice, the system is composed by a package of software products used as add-ons to the main management information system of the company. A comprehensive and detailed description of the approach, techniques used and developed algorithms is presented. The experience in using a first prototype of the system shows this may become a highly valuable computer tool in production planning, layout design and assignment of orders.
Computational Optimization and Applications | 2010
Bernardo Almada-Lobo; Diego Klabjan; Maria Antónia Carravilla; José Fernando Oliveira
We address the short-term production planning and scheduling problem coming from the glass container industry. A furnace melts the glass that is distributed to a set of parallel molding machines. Both furnace and machine idleness are not allowed. The resulting multi-machine multi-item continuous setup lotsizing problem with a common resource has sequence-dependent setup times and costs. Production losses are penalized in the objective function since we deal with a capital intensive industry. We present two mixed integer programming formulations for this problem, which are reduced to a network flow type problem. The two formulations are improved by adding valid inequalities that lead to good lower bounds. We rely on a Lagrangian decomposition based heuristic for generating good feasible solutions. We report computational experiments for randomly generated instances and for real-life data on the aforementioned problem, as well as on a discrete lotsizing and scheduling version.
International Transactions in Operational Research | 2003
Maria Antónia Carravilla; Cristina Ribeiro; José Fernando Oliveira
In this paper an application of constraint logic programming (CLP) to the resolution of nesting problems is presented. Nesting problems are a special case of the cutting and packing problems, in which the pieces generally have non-convex shapes. Due to their combinatorial optimization nature, nesting problems have traditionally been tackled by heuristics and in the recent past by meta-heuristics. When trying to formulate nesting problems as linear programming models, to achieve global optimal solutions, the difficulty of dealing with the disjunction of constraints arises. On the contrary, CLP deals easily with this type of relationships among constraints. A CLP implementation for the nesting problem is described for convex and non-convex shapes. The concept of no-fit polygon is used to deal with the geometric constraints inherent to all cutting and packing problems. Computational results are presented.
Computers & Operations Research | 2008
Bernardo Almada-Lobo; José Fernando Oliveira; Maria Antónia Carravilla
Gupta and Magnusson [The capacitated lot-sizing and scheduling problem with sequence-dependent setup costs and setup times. Computers and Operations Research 2005;32(4):727-47] develop a model for the single machine capacitated lot-sizing and scheduling problem (CLSP) with sequence dependent setup times and setup costs, incorporating all the usual features of setup carryovers. In this note we show that this model does not avoid disconnected subtours. A new set of constraints is added to the model to provide an exact formulation for this problem.
European Journal of Operational Research | 2016
Luiz Henrique Cherri; Leandro Resende Mundim; Marina Andretta; Franklina Maria Bragion Toledo; José Fernando Oliveira; Maria Antónia Carravilla
Two-dimensional irregular strip packing problems are cutting and packing problems where small pieces have to be cut from a larger object, involving a non-trivial handling of geometry. Increasingly sophisticated and complex heuristic approaches have been developed to address these problems but, despite the apparently good quality of the solutions, there is no guarantee of optimality. Therefore, mixed-integer linear programming (MIP) models started to be developed. However, these models are heavily limited by the complexity of the geometry handling algorithms needed for the piece non-overlapping constraints. This led to pieces simplifications to specialize the developed mathematical models. In this paper, to overcome these limitations, two robust MIP models are proposed. In the first model (DTM) the non-overlapping constraints are stated based on direct trigonometry, while in the second model (NFP−CM) pieces are first decomposed into convex parts and then the non-overlapping constraints are written based on nofit polygons of the convex parts. Both approaches are robust in terms of the type of geometries they can address, considering any kind of non-convex polygon with or without holes. They are also simpler to implement than previous models. This simplicity allowed to consider, for the first time, a variant of the models that deals with piece rotations. Computational experiments with benchmark instances show that NFP−CM outperforms both DTM and the best exact model published in the literature. New real-world based instances with more complex geometries are proposed and used to verify the robustness of the new models.
Journal of Scheduling | 2013
Marta Rocha; José Fernando Oliveira; Maria Antónia Carravilla
In this work, we propose a general integer programming model to address the staff scheduling problem, flexible enough to be easily adapted to a wide-range of real-world problems. The model is applied with slight changes to two case studies: a glass plant and a continuous care unit, and also to a collection of benchmark instances available in the literature. The emphasis of our approach is on a novel formulation of sequence constraints and also on workload balance, which is tackled through cyclic scheduling. Models are solved using the CPLEX solver. Computational results indicate that optimal solutions can be achieved within a reasonable amount of time.
European Journal of Operational Research | 2014
Beatriz Brito Oliveira; Maria Antónia Carravilla; José Fernando Oliveira; Franklina Maria Bragion Toledo
Empty repositions are a major problem for car rental companies that deal with special types of vehicles whose number of units is small. In order to meet reservation requirements concerning time and location, companies are forced to transfer cars between rental stations, bearing significant costs and increasing the environmental impact of their activity due to the fuel consumption and CO2 emission. In this paper, this problem is tackled under a vehicle-reservation assignment framework as a network-flow model in which the profit is maximized. The reservations are allocated considering the initial and future availability of each car, interdependencies between rental groups, and different reservation priorities. To solve this model, a relax-and-fix heuristic procedure is proposed, including a constraint based on local branching that enables and controls modifications between iterations. Using real instances, the value of this approach is established and an improvement of 33% was achieved when compared to the company’s current practices.
International Journal of Production Research | 2016
Aline Aparecida de Souza Leão; Franklina Maria Bragion Toledo; José Fernando Oliveira; Maria Antónia Carravilla
Solving nesting problems involves the waste minimisation in cutting processes, and therefore it is not only economically relevant for many industries but has also an important environmental impact, as the raw materials that are cut are usually a natural resource. However, very few exact approaches have been proposed in the literature for the nesting problem (also known as irregular packing problem), and the majority of the known approaches are heuristic algorithms, leading to suboptimal solutions. The few mathematical programming models known for this problem can be divided into discrete and continuous models, based on how the placement coordinates of the pieces to be cut are dealt with. In this paper, we propose an innovative semi-continuous mixed-integer programming model for two-dimensional cutting and packing problems with irregular shaped pieces. The model aims to exploit the advantages of the two previous classes of approaches and discretises the -axis while keeping the -coordinate continuous. The board can therefore be seen as a set of stripes. Computational results show that the model, when solved by a commercial solver, can deal with large problems and determine the optimal solution for smaller instances, but as it happens with discrete models, the optimal solution value depends on the discretisation step that is used.
European Journal of Engineering Education | 2004
Maria Antónia Carravilla; José Fernando Oliveira
This paper describes a case study concerning the teaching of logistics in the Computers and Electrical Engineering degree at FEUP. The logistics course is taken in the last semester of the degree and there are no lectures given by the teachers. All the learning strategy is based upon the autonomous learning capacity of the students, following the widespread citation of Confucius, ‘I hear and I forget. I see and I remember. I do and I understand’. The students are organized in groups and their autonomous work is motivated by the presentation that each group leader has to give every other week. A discussion period follows each presentation, and can be used by the teachers to evaluate the involvement of each member of the group and to complement the presentation whenever necessary. All the students are leaders at least once. The leaders are responsible for the group management and must prepare for the ‘leaders’ meeting, where the presentation session is organized. Assessment is based both on the quality of the presentation and on the technical correctness and completeness in the way subjects are treated and on leadership skills. While the teachers evaluate the two first issues, peers evaluate leadership.