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...

microgrids are small-scale, low voltage (lv) power networks which employ renewable distribution energy resources (ders) with power electronic interfaces (peis). microgrids as single controlled units and active distribution networks require flexible control systems to ensure reliable and secure operation in different modes. these various operations of microgrid cause variations in voltage and fr...

The (semi)standard Young tableau have been known since Hodge and Littlewood to naturally index a basis for the multihomogeneous coordinate rings of flag varieties under the Plücker embedding. In representation theory, the irreducible representations of GLn(C) arise as the multihomogeneous components of these rings. I introduce a new class of straight tableau by slightly weakening the requiremen...

we present an improved implementation of the wagner-whitin algorithm for economic lot-sizing problems based on the planning-horizon theorem and the economic- part-period concept. the proposed method of this paper reduces the burden of the computations significantly in two different cases. we first assume there is no backlogging and inventory holding and set-up costs are fixed. the second model ...

clustering is a widespread data analysis and data mining technique in many fields of study such as engineering, medicine, biology and the like. the aim of clustering is to collect data points. in this paper, a cultural algorithm (ca) is presented to optimize partition with n objects into k clusters. the ca is one of the effective methods for searching into the problem space in order to find a n...

optimization of cutting conditions is a non-linear optimization with constraint and it is very important to the increase of productivity and the reduction of costs. in recent years, several evolutionary and meta-heuristic optimization algorithms were introduced. the cuckoo optimization algorithm (coa) is one of several recent and powerful meta-heuristics which is inspired by the cuckoos and the...

in this paper, we study the generalized bin covering problem. for this problem an exact algorithm is introduced which can nd optimal solution for small scale instances. to nd a solution near optimal for large scale instances, a heuristic algorithm has been proposed. by computational experiments, the eciency of the heuristic algorithm is assessed.

cloud computing is the latest technology that involves distributed computation over the internet. it meets the needs of users through sharing resources and using virtual technology. the workflow user applications refer to a set of tasks to be processed within the cloud environment. scheduling algorithms have a lot to do with the efficiency of cloud computing environments through selection of su...

abstract— in this paper we have tried to develop an altered version of the artificial bee colony algorithm which is inspired from and combined with the meta-heuristic algorithm of firefly. in this method, we have tried to change the main equation of searching within the original abc algorithm. on this basis, a new combined equation was used for steps of employed bees and onlooker bees. for this...