clustering is an effective approach for managing nodes in wireless sensor network (wsn). a new method of clustering mechanism with using binary gravitational search algorithm (bgsa) in wsn, is proposed in this paper to improve the energy consumption of the sensor nodes.reducing the energy consumption of sensors in wsnsis the objective of this paper that is through selecting thesub optimum senso...

In this paper we present an approach for the optimization of ordered Binary Decision Diagrams (OBDDs), based on Genetic Algorithms. In this method we consider completely specified Boolen Functions (BFs). The method uses specific reordering heuristics [3] and combines them with principles of genetic algorithms in order to determine a good variable ordering. Only small populations are considered ...

In this paper we propose a methodology based on a genetic algorithm (GA) to automate the design of combinational logic circuits in which we aim to minimize the total number of gates used. Our results are compared against those produced by human designers and by another GA-based approach. We also analyze the importance of using a non-binary representation in this problem despite the commonly acc...

Binary Decision Diagrams (BDDs) have proved to be a powerful representation for Boolean functions. Particularly, they are a very useful data structure for the symbolic model checking of digital circuits and other finite state systems, as well as other problems. Nevertheless, the size of the BDD representation of these functions is highly dependent on the order of the function arguments, also ca...

in this paper, we present a genetic algorithm (ga) for optimization of a multi-mode resource constrained time cost trade off (mrctct) problem. the proposed ga, each activity has several operational modes and each mode identifies a possible executive time and cost of the activity. beyond earlier studies on time-cost trade-off problem, in mrctct problem, resource requirements of each execution mo...

Scheduling problems have the standard consideration in the field of manufacturing. Among the various types of scheduling problems, the job shop scheduling problem is one of the most interesting NP-hard problems. As the job shop scheduling is an optimization problem, Genetic algorithm was selected to solve it In this study. Selection scheme is one of the important operators of Genetic algorithm....

background : in medical studies, when the joint prediction about occurrence of two events should be anticipated, a statistical bivariate model is used. due to the limitations of usual statistical models, other methods such as artificial neural network (ann) and hybrid models could be used. in this paper, we propose a hybrid artificial neural network-genetic algorithm (ann-ga) model to predictio...

This report is based on the work I have done for my Master Thesis project. The project as a whole consists of research done in the eld of evolutionary computation, and it is split into two distinct parts. The main theme is adaptive evolutionary algorithms. The rst part covers the research done on solving binary constraint satisfaction problems using adaptive evolutionary algorithms. This involv...

Seismic imaging, popularly known as tomography, borrowing the term from medical sciences, produces the raster image of the internal structure by combining information from a set of projections obtained at different viewing angles. To engineer high resolution and accurate solutions to mining problems, seismic traveltime tomography can yield a high resolution image of the subsurface to provide in...