multiple traveling salesman problem (mtsp) is one of the most popular operation research problem and is known as combinatorial optimization problems. mtsp is an extension version of the famous and widely used problem named traveling salesman problem (tsp). because of its benefices in various domains, many researchers have tried to solve that, and many methods have proposed so far. mtsp is a np-...

cardiovascular diseases are one of the most common diseases that cause a large number of deaths each year. coronary artery disease (cad) is the most common type of these diseases worldwide and is the main reason of heart attacks. thus early diagnosis of cad is very essential and is an important field of medical studies. many methods are used to diagnose cad so far. these methods reduce cost and...

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...

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.