To improve the protein folding simulations, polymorphic bacterial chemotaxis optimization (PBCO) was investigated on a 2D lattice model. PBCO is a novel intelligent problem solving technique inspired from the foraging behavior of bacteria. We compared PBCO with standard genetic algorithm (SGA) and Immune Genetic Algorithm (IGA) for various chain lengths. It shows that PBCO has the highest succe...

many qtls related to agronomic triats have been registered in soybean (glycine max) by different research groups during the last decade. due to the interaction effects of qtls, environmental and genetic backgrounds on the emergence of qtls and also to confirm the previous results as well as to identify new qtls, further studies are still required. in order to map qtl which control some agronomi...

evolutionary algorithms are some of the most crucial random approaches tosolve the problems, but sometimes generate low quality solutions. on the otherhand, learning automata are adaptive decision-making devices, operating onunknown random environments, so it seems that if evolutionary and learningautomaton based algorithms are operated simultaneously, the quality of results willincrease sharpl...

determining the optimal location of wells with the aid of an automated search algorithm is a significant and difficult step in the reservoir development process. it is a computationally intensive task due to the large number of simulation runs required. therefore,the key issue to such automatic optimization is development of algorithms that can find acceptable solutions with a minimum number of...

This paper introduces the optimization algorithm to improve search rate in urban path routing problems using viral infection and local search in urban environment. This algorithm operates based on two different approaches including wavelet transform and genetic algorithm. The variables proposed by driver such as degree of difficulty and difficulty traffic are of the essence in this technique. W...

in this paper, a stochastic cell formation problem is studied using queuing theory framework and considering reliability. since cell formation problem is np-hard, two algorithms based on genetic and modified particle swarm optimization (mpso) algorithms are developed to solve the problem. for generating initial solutions in these algorithms, a new heuristic method is developed, which always cre...