in this paper, a multi-objective reconfiguration problem has been solved simultaneously by a modified ant colony optimization algorithm. two objective functions, real power loss and energy not supplied index (ens), were utilized. multi-objective modified ant colony optimization algorithm has been generated by adding non-dominated sorting technique and changing the pheromone updating rule of ori...

fuzzy clustering methods are conveniently employed in constructing a fuzzy model of a system, but they need to tune some parameters. in this research, fcm is chosen for fuzzy clustering. parameters such as the number of clusters and the value of fuzzifier significantly influence the extent of generalization of the fuzzy model. these two parameters require tuning to reduce the overfitting in the...

scheduling for job shop is very important in both fields of production management and combinatorial op-timization. however, it is quite difficult to achieve an optimal solution to this problem with traditional opti-mization approaches owing to the high computational complexity. the combination of several optimization criteria induces additional complexity and new problems. in this paper, we pro...

this paper focuses on multi-objective designing of multi-machine thyristor controlled series compensator (tcsc) using strength pareto evolutionary algorithm (spea). the tcsc parameters designing problem is converted to an optimization problem with the multi-objective function including the desired damping factor and the desired damping ratio of the power system modes, which is solved by a spea ...

Resource allocation is the optimal distribution in a limited number of resources available for certain activities. The large activities requires exponentially multiplying computation cost. Therefore, resource problem known as NP-Hard literature. In this study, multi-objective binary artificial bee colony algorithm has been proposed solving problems. benefited from robust structure and easy impl...

Abstract In many real-world situations, we have to deal with multiple objectives simultaneously in order make appropriate decisions. The presence of an optimization problem makes the challenging because most time these are conflicting nature. For example, may want maximize return on investment a portfolio and, other hand, minimize risk associated assets portfolio. We cost product while maximizi...