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Publications

Publications by Maria Antónia Carravilla

2018

A Dynamic Programming Approach for Integrating Dynamic Pricing and Capacity Decisions in a Rental Context

Authors
Oliveira, BB; Carravilla, MA; Oliveira, JF;

Publication
OPERATIONAL RESEARCH

Abstract
Car rental companies have the ability and potential to integrate their dynamic pricing decisions with their capacity decisions. Pricing has a significant impact on demand, while capacity, which translates fleet size, acquisition planning and fleet deployment throughout the network, can be used to meet this price-sensitive demand. Dynamic programming has been often used to tackle dynamic pricing problems and also to deal with similar integrated problems, yet with some significant differences as far as the inventory depletion and replenishment are considered. The goal of this work is to understand what makes the car rental problem different and hinders the application of more common methods. To do so, a discrete dynamic programming framework is proposed, with two different approaches to calculate the optimal-value function: one based on a Mixed Integer Non Linear Program (MINLP) and one based on a Constraint Programming (CP) model. These two approaches are analyzed and relevant insights are derived regarding the (in)ability of discrete dynamic programming to effectively tackle this problem within a rental context when realistically sized instances are considered.

2018

Understanding Complexity in a Practical Combinatorial Problem Using Mathematical Programming and Constraint Programming

Authors
Oliveira, BB; Carravilla, MA;

Publication
OPERATIONAL RESEARCH

Abstract
Optimization problems that are motivated by real-world settings are often complex to solve. Bridging the gap between theory and practice in this field starts by understanding the causes of complexity of each problem and measuring its impact in order to make better decisions on approaches and methods. The Job-Shop Scheduling Problem (JSSP) is a well-known complex combinatorial problem with several industrial applications. This problem is used to analyse what makes some instances difficult to solve for a commonly used solution approach - Mathematical Integer Programming (MIP) - and to compare the power of an alternative approach: Constraint Programming (CP). The causes of complexity are analysed and compared for both approaches and a measure of MIP complexity is proposed, based on the concept of load per machine. Also, the impact of problem-specific global constraints in CP modelling is analysed, making proof of the industrial practical interest of commercially available CP models for the JSSP.

2013

Cyclic staff scheduling: optimization models for some real-life problems

Authors
Rocha, M; Oliveira, JF; Carravilla, MA;

Publication
JOURNAL OF SCHEDULING

Abstract
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.

2018

A general heuristic for two-dimensional nesting problems with limited-size containers

Authors
Mundim, LR; Andretta, M; Carravilla, MA; Oliveira, JF;

Publication
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH

Abstract
Cutting raw-material into smaller parts is a fundamental phase of many production processes. These operations originate raw-material waste that can be minimised. These problems have a strong economic and ecological impact and their proper solving is essential to many sectors of the economy, such as the textile, footwear, automotive and shipbuilding industries, to mention only a few. Two-dimensional (2D) nesting problems, in particular, deal with the cutting of irregularly shaped pieces from a set of larger containers, so that either the waste is minimised or the value of the pieces actually cut from the containers is maximised. Despite the real-world practical relevance of these problems, very few approaches have been proposed capable of dealing with concrete characteristics that arise in practice. In this paper, we propose a new general heuristic (H4NP) for all 2D nesting problems with limited-size containers: the Placement problem, the Knapsack problem, the Cutting Stock problem, and the Bin Packing problem. Extensive computational experiments were run on a total of 1100 instances. H4NP obtained equal or better solutions for 73% of the instances for which there were previous results against which to compare, and new benchmarks are proposed.

2017

Cutting and Packing

Authors
Alvarez-Valdes, R; Carravilla, MA; Oliveira, JF;

Publication
Handbook of Heuristics

Abstract

2018

Resources for the Education in Operations Research: Past, Present and Future

Authors
Carravilla, MA; Oliveira, JF;

Publication
Lecture Notes in Logistics

Abstract
In this chapter, we outline the issue of education in the field of Operations Research (OR) and discuss various educational resources that are currently available, with a main focus on the most important international resources, but also with an emphasis on what is currently done in our home country, Portugal. The identification of shortcomings of education in OR and opportunities for its development will follow from the analysis of these resources. By choosing the word “education” over “teaching”, the aim is to stress the fact that (formal) teaching is nothing but one of the multiple aspects of education, whatever the field may be. Finally, we conclude that the dissemination and promotion of the field of OR intimately relates to issues related to education in this field. It is shown that these activities create a direct impact on the ability to attract publics into educational activities in this area, such as students enrolment on courses and programs with a high OR content. © 2018, Springer International Publishing AG.

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