Multi-objective optimization methods are essential to resolve real-world problems as most involve several types of objects. Several multi-objective genetic algorithms have been proposed. Among them, SPEA2 and NSGA-II are the most successful. In the present study, two new mechanisms were added to SPEA2 to improve its searching ability a more effective crossover mechanism and an archive mechanism...

In this article, we view the Pareto and weak solutions of multiobjective optimization by using an approximate version KKT type conditions. one our main results Ekeland’s variational principle for vector-valued maps plays a key role. We also focus on improved Geoffrion proper it’s approximation characterize them through saddle point

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...

This paper proposes the exchange market algorithm (EMA) to solve the combined economic and emission dispatch (CEED) problems in thermal power plants. The EMA is a new, robust and efficient algorithm to exploit the global optimum point in optimization problems. Existence of two seeking operators in EMA provides a high ability in exploiting global optimum point. In order to show the capabilities ...

Design is a multi-objective decision-making process considering manufacturing, cost, aesthetics, usability among many other product attributes. The set of optimal solutions, the Pareto set, indicates the tradeoffs between objectives. Decision-makers generally select their own optima from the Pareto set based on personal preferences or other judgements. However, uncertainties from manufacturing ...

Many practical optimization problems usually have several conflicting objectives. In those multi-objective optimization, no solution optimizing all objective functions simultaneously exists in general. Instead, Pareto optimal solutions, which are “efficient” in terms of all objective functions, are introduced. In general we have many Pareto optimal solutions. Therefore, we need to decide a fina...