Trends and impact of forest tenure reforms in Asia: cases from India, Indonesia, Lao PDR, Nepal and the Philippines

For the last two decades, some countries in Asia have initiated progressive tenure reform in the forestry sector through transfer of management and use rights from the state to the local communities, indigenous groups, local government units, private sector and individual households. However, still around 92% of the forests in South and Southeast Asia are owned by the state, which manages it particularly for revenue generation and protection of environment (FAO 2006). Some of the devolved tenure models such as community forestry in Nepal and the Philippines and joint forest management in India are yielding promising results in terms of forest protection, but the livelihoods of the local communities are not fully recognized yet. Decentralization of forest management rights at household level such as in China, Vietnam and Cambodia is another encouraging model as it contributes to raising the incomes of poor households. However, the security of such rights in legal terms is questionable due to inconsistent policies and legal frameworks. Tenure reforms in Asia have had mixed results so far, but the reforms are heading towards addressing peoples’ livelihood needs on the one hand and protecting forest and environment on the other

Bridging, linking, and bonding social capital in collective action: the case of Kalahan forest reserve in the Philippines

This paper seeks to identify the factors which are responsible for successful management of natural resources when communities are given opportunities to manage those resources. Applying the social capital framework, it analyzes empirical data from the well known case of Kalahan Educational Foundation, the Philippines. The study confirms previous findings, which have emphasized the high level of cohesion and traditional norms among a homogeneous community of indigenous peoples (bonding social capital) as a success factor. This study further identifies that for effective management of collective action, mobilization of bridging and linking social capital are equally important as they do not only help mobilize external resources but, at times, also promote bonding social capital

GA/SA-based hybrid techniques for the scheduling of generator maintenance in power systems

Proposes the application of a genetic algorithm (GA) and simulated annealing (SA) based hybrid approach for the scheduling of generator maintenance in power systems using an integer representation. The adapted approach uses the probabilistic acceptance criterion of simulated annealing within the genetic algorithm framework. A case study is formulated in this paper as an integer programming problem using a reliability-based objective function and typical problem constraints. The implementation and performance of the solution technique are discussed. The results in this paper demonstrate that the technique is more effective than approaches based solely on genetic algorithms or solely on simulated annealing. It therefore proves to be a valid approach for the solution of generator maintenance scheduling problem

Developing Culturally Contextualised Mathematics Resource Materials: Capturing Local Practices of Tamang and Gopali Communities

Setting out to develop culturally contextualised curriculum support materials for teachers and students and a material for parental awareness, the project produced five sets of support materials incorporating the cultural practices of Tamang and Gopali communities. By following a two-phase procedural strategy the project demonstrated a unique possibility of integrating Nepali local cultural practices in school mathematics curriculum

A knowledge-based genetic algorithm for unit commitment

NoA genetic algorithm (GA) augmented with knowledge-based methods has been developed for solving the unit commitment economic dispatch problem. The GA evolves a population of binary strings which represent commitment schedules. The initial population of schedules is chosen using a method based on elicited scheduling knowledge. A fast rule-based dispatch method is then used to evaluate candidate solutions. The knowledge-based genetic algorithm is applied to a test system of ten thermal units over 24-hour time intervals, including minimum on/off times and ramp rates, and achieves lower cost solutions than Lagrangian relaxation in comparable computational time

Fuzzy Multiple Heuristic Ordering for Examination Timetabling

In this paper, we address the issue of ordering exams by simultaneously considering two separate heuristics using fuzzy methods. Combinations of two of the following three heuristic orderings are employed: largest degree, saturation degree and largest enrolment. The fuzzy weight of an exam is used to represent how difficult it is to schedule. The decreasingly ordered exams are sequentially chosen to be assigned to the last slot with least penalty cost value while the feasibility of the timetable is maintained throughout the process. Unscheduling and rescheduling exams is performed until all exams are scheduled. The proposed algorithm has been tested on 12 benchmark examination timetabling data sets and the results show that this approach can produce good quality solutions. Moreover, there is significant potential to extend the approach by including a larger range of heuristics