Monteiro, Regina C. C., Andreia A. S. Lopes, Maria M. A. Lima, Joao P. Veiga, Rui JC Silva, Carlos J. Dias, Erika J. R. Davim, and Maria H. V. Fernandes. "
Sintering, Crystallization, and Dielectric Behavior of Barium Zinc Borosilicate GlassesuEffect of Barium Oxide Substitution for Zinc Oxide."
Journal of the American Ceramic Society. 95.10 (2012): 3144-3150.
Abstractn/a
Goulão, Miguel, Nelson Fonte, Michel Wermelinger, and Fernando Brito Abreu. "
Software Evolution Prediction Using Seasonal Time Analysis: a Comparative Study."
16th European Conference on Software Maintenance and Reengineering (CSMR 2012). Szeged, Hungary: IEEE Computer Society, 2012.
AbstractPrediction models of software change requests are useful for supporting rational and timely resource
allocation to the evolution process. In this paper we use a time series forecasting model to predict software
maintenance and evolution requests in an open source software project (Eclipse), as an example of projects with seasonal release cycles. We build an ARIMA model based on data collected from Eclipse’s change request tracking system since the project’s start. A change request may refer to defects found in the software, but also to suggested improvements in the system under scrutiny. Our model includes the identification of seasonal patterns and tendencies, and is validated through the forecast of the change requests evolution for the next 12 months. The usage of seasonal information significantly improves the estimation ability of this model, when compared to other ARIMA models found in the literature, and does so for a much longer estimation period. Being able to accurately forecast the change requests’ evolution over a fairly long time period is an important ability for enabling adequate process control in maintenance activities, and facilitates
effort estimation and timely resources allocation. The approach presented in this paper is suitable for projects with a relatively long history, as the model building process relies on historic data.
Esteves, V. M. C., J. M. C. Sousa, C. A. Silva, A. P. B. Povoa, and M. I. Gomes. "
SCant-design: Closed loop supply chain design using ant colony optimization."
2012 IEEE Congress on Evolutionary Computation (CEC). Brisbane, Australia 2012.
AbstractThis paper proposes a new optimization methodology for supply chain design, using ant colony optimization. The objective of this methodology is to choose the facilities that will take part in a multi-product closed-loop supply chain, such as factories, warehouses and disassembly centers, in order to minimize the costs related to these facilities and those related to transportation costs, both in the forward and reverse chains. Considering that total production quantities for factories, expected cross-docking stocks for warehouses, and disassembly centers are determined by this methodology, it can be considered that it undertakes both strategic and tactical Supply Chain Management (SCM) problems at once. The developed algorithm, SCant-Design, is sufficiently general to solve any SCM configuration, with linear and nonlinear cost functions and constraints. The algorithm results were compared to a MILP approach for a particular case study and the obtained value for the cost function is very similar, although using less facilities.