In general, Multi-objective Evolutionary Algorithms do not guarantee find solutions in the Pareto-optimal set. We propose a new approach for solving decomposable deceptive multi-objective problems that can find all solutions of the Pareto-optimal set. Basically, the proposed approach starts by decomposing the problem into subproblems and, then, combining the found solutions. The resultant appro...

one of the most important applications of multi-objective optimization is adjusting parameters ofpractical engineering problems in order to produce a more desirable outcome. in this paper, the decoupled sliding mode control technique (dsmc) is employed to stabilize an inverted pendulum which is a classic example of inherently unstable systems. furthermore, a new multi-objective particle swarm o...

because the underlying physiology of pathological tremor in a parkinson's patient is not well understood, the existing physical and drug therapies have not been successful in tremor treatment. different mathematical modeling of such vibration has been introduced to investigate the problem and reduce the existing vibration. most of the models have represented the induced vibration as a sinusoida...

application of either protein or carbohydrate-based products as fat replacers in low fat ice-creams can improve the properties of these products. however, the type and level of fat and fat replacer utilized are affected by such different parameters as functional ones, namely: viscosity and overrun, hardness and melting rate, nutritional properties (calories) as well as the price of the final pr...

this paper deals with a bi-objective hybrid no-wait flowshop scheduling problem minimizing the makespan and total weighted tardiness, in which we consider transportation times between stages. obtaining an optimal solution for this type of complex, large-sized problem in reasonable computational time by using traditional approaches and optimization tools is extremely difficult. this paper presen...

This paper introduces a method for solving multi-objective optimization problems in uncertain environment. When the uncertainty factors of the optimization problem can be included into the mathematical model, through bounded intervals, [I]RMOA (Interval Robust Multi-objective Algorithm) can find an enclosure of the robust Pareto frontier. In this approach, the robust Pareto solutions are the on...

In this work, a new multi-objective optimization algorithm called learner performance-based behavior is proposed. The proposed based on the process of moving graduated students from high school to college. technique produces set non-dominated solutions. To test ability and efficacy algorithm, it applied group benchmarks five real-world engineering problems. Several widely used metrics are emplo...

In this paper multi objective optimization problem for partitioning process of VLSI circuit optimization is solved using IPO algorithm. The methodology used in this paper is based upon the dynamic of sliding motion along a frictionless inclined plane. In this work, modules and elements of the circuit are divided into two smaller parts (components) in order to minimize the cutsize and area imbal...