Identifying sources of global contention in constraint satisfaction search

Much work has been done on learning from failure in search to boost solving of combinatorial problems, such as clause-learning and clause-weighting in boolean satisfiability (SAT), nogood and explanation-based learning, and constraint weighting in constraint satisfaction problems (CSPs). Many of the top solvers in SAT use clause learning to good effect. A similar approach (nogood learning) has not had as large an impact in CSPs. Constraint weighting is a less fine-grained approach where the information learnt gives an approximation as to which variables may be the sources of greatest contention. In this work we present two methods for learning from search using restarts, in order to identify these critical variables prior to solving. Both methods are based on the conflict-directed heuristic (weighted-degree heuristic) introduced by Boussemart et al. and are aimed at producing a better-informed version of the heuristic by gathering information through restarting and probing of the search space prior to solving, while minimizing the overhead of these restarts. We further examine the impact of different sampling strategies and different measurements of contention, and assess different restarting strategies for the heuristic. Finally, two applications for constraint weighting are considered in detail: dynamic constraint satisfaction problems and unary resource scheduling problems.

Impact of protected forests on rural household fuel tree planting and deforestation: Chiro District, Ethiopia

This study aims at exploring the potential impact of forest protection intervention on rural households’ private fuel tree planting in Chiro district of eastern Ethiopia. The study results revealed a robust and significant positive impact of the intervention on farmers’ decisions to produce private household energy by growing fuel trees on their farm. As participation in private fuel tree planting is not random, the study confronts a methodological issue in investigating the causal effect of forest protection intervention on rural farm households’ private fuel tree planting through non-parametric propensity score matching (PSM) method. The protection intervention on average has increased fuel tree planting by 503 (580.6%) compared to open access areas and indirectly contributed to slowing down the loss of biodiversity in the area. Land cover/use is a dynamic phenomenon that changes with time and space due to anthropogenic pressure and development. Forest cover and land use changes in Chiro District, Ethiopia over a period of 40 years was studied using remotely sensed data. Multi temporal satellite data of Landsat was used to map and monitor forest cover and land use changes occurred during three point of time of 1972,1986 and 2012. A pixel base supervised image classification was used to map land use land cover classes for maps of both time set. The result of change detection analysis revealed that the area has shown a remarkable land cover/land use changes in general and forest cover change in particular. Specifically, the dense forest cover land declined from 235 ha in 1972 to 51 ha in 1986. However, government interventions in forest protection in 1989 have slowed down the drastic change of dense forest cover loss around the protected area through reclaiming 1,300 hectares of deforested land through reforestation program up to 2012.