A genetic algorithm for project scheduling with multi-modes and renewable resources

This paper presents a genetic algorithm-based approach for project scheduling with multi-modes and renewable resources. In this problem activities of the project may be executed in more than one operating mode and renewable resource constraints are imposed. The objective function is the minimization of the project completion time. The idea of this approach is integrating a genetic algorithm with a schedule generation scheme. This study also proposes applying a local search procedure trying to yield a better solution when the genetic algorithm and the schedule generation scheme obtain a solution. The experimental results show that this algorithm is an effective method for solving this problem.

Levels and risks of particulate-bound PAHs in indoor air influenced by tobacco smoke: a field measurement

Considering tobacco smoke as one of the most health-relevant indoor sources, the aim of this work was to further understand its negative impacts on human health. The specific objectives of this work were to evaluate the levels of particulate-bound PAHs in smoking and non-smoking homes and to assess the risks associated with inhalation exposure to these compounds. The developed work concerned the application of the toxicity equivalency factors approach (including the estimation of the lifetime lung cancer risks, WHO) and the methodology established by USEPA (considering three different age categories) to 18 PAHs detected in inhalable (PM10) and fine (PM2.5) particles at two homes. The total concentrations of 18 PAHs (ΣPAHs) was 17.1 and 16.6 ng m−3 in PM10 and PM2.5 at smoking home and 7.60 and 7.16 ng m−3 in PM10 and PM2.5 at non-smoking one. Compounds with five and six rings composed the majority of the particulate PAHs content (i.e., 73 and 78 % of ΣPAHs at the smoking and non-smoking home, respectively). Target carcinogenic risks exceeded USEPA health-based guideline at smoking home for 2 different age categories. Estimated values of lifetime lung cancer risks largely exceeded (68–200 times) the health-based guideline levels at both homes thus demonstrating that long-term exposure to PAHs at the respective levels would eventually cause risk of developing cancer. The high determined values of cancer risks in the absence of smoking were probably caused by contribution of PAHs from outdoor sources.

A Learning Algorithm and System Approach to Address Exceptional Events in Domestic Consumption Management

The integration of the Smart Grid concept into the electric grid brings to the need for an active participation of small and medium players. This active participation can be achieved using decentralized decisions, in which the end consumer can manage loads regarding the Smart Grid needs. The management of loads must handle the users’ preferences, wills and needs. However, the users’ preferences, wills and needs can suffer changes when faced with exceptional events. This paper proposes the integration of exceptional events into the SCADA House Intelligent Management (SHIM) system developed by the authors, to handle machine learning issues in the domestic consumption context. An illustrative application and learning case study is provided in this paper.