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...

Data clustering is the process of partitioning a set of data objects into meaning clusters or groups. Due to the vast usage of clustering algorithms in many fields, a lot of research is still going on to find the best and efficient clustering algorithm. K-means is simple and easy to implement, but it suffers from initialization of cluster center and hence trapped in local optimum. In this paper...

The traveling salesman problem (TSP) is one of the most important combinational optimization problems that have nowadays received much attention because of its practical applications in industrial and service problems. In this paper, a hybrid two-phase meta-heuristic algorithm called MACSGA used for solving the TSP is presented. At the first stage, the TSP is solved by the modified ant colony s...

The Optimal Power Flow (OPF) is one of the most important issues in the power systems. Due to the complexity and discontinuity of some parameters of power systems, the classic mathematical methods are not proper for this problem. In this paper, the objective function of OPF is formulated to minimize the power losses of transmission grid and the cost of energy generation and improve the voltage ...

the multiple traveling salesman problem (mtsp) involves scheduling m > 1 salesmen to visit a set of n > m nodes so that each node is visited exactly once. the objective is to minimize the total distance traveled by all the salesmen. the mtsp is an example of combinatorial optimization problems, and has a multiplicity of applications, mostly in the areas of routing and scheduling. in this paper,...

Due to the variety of products, simultaneous production of different models has an important role in production systems. Moreover, considering the realistic constraints in designing production lines attracted a lot of attentions in recent researches. Since the assembly line balancing problem is NP-hard, efficient methods are needed to solve this kind of problems. In this study, a new hybrid met...

In this paper, a hybrid meta-heuristic algorithm, based on imperialistic competition algorithm (ICA), harmony search (HS), and simulated annealing (SA) is presented. The body of the proposed hybrid algorithm is based on ICA. The proposed hybrid algorithm inherits the advantages of the process of harmony creation in HS algorithm to improve the exploitation phase of the ICA algorithm. In addition...

in this paper, the distribution network for multi-level supply chain has been studied. products produced in factories are sent to customers through warehouses and distribution centers based on specific demands. warehouses as holding inventory facilities are located close to factories and the distribution centers are placed in the most accessible locations for services near customers. each item ...

Fault diagnosis based on the expert system (ES) is still a research topic of manufacturing in Industry 4.0 because stronger interpretability. As core component ES, fault accuracy positively correlated to precise knowledge base. But it difficult for users understand obtained from original dataset utilizing existing extraction method. Therefore, great significance extract easy-to-understand and e...