 Evolutionary multi-objective optimization (EMOO) finds a set of Pareto solutions rather than any single aggregated optimal solution for a multi-objective problem. The purpose of this paper is to describe a newly developed evolutionary approach --Paretobased multi-objective differential evolution (MODE). In this paper, the concept of differential evolution, which is well-known in the continuou...

Omni-optimization assumes a capability to perform any type of optimization, e.g. singleand multi-objective, using single optimization algorithm, or the omni-optimizer. This paper addresses a novel concept for omni-optimization, by coupling vectorization with genetic algorithms (GAs). Vectorization assumes converting constraints into objectives, and their optimization alongside the original set ...

This chapter presents three MS Excel programs, namely, EMOO (Excel based Multi-Objective Optimization), NDS (Non-Dominated Sorting) and PM (Performance Metrics) useful for Multi-Objective Optimization (MOO) studies. The EMOO program is for finding non-dominated solutions of a given MOO problem. It has both binary-coded and realcoded NSGA-II (Elitist Non-Dominated Sorting Genetic Algorithm), and...

the purpose of this paper is multi-objective optimization of refrigeration cycle by optimization of all components of the cycle contains heat exchangers, air condenser, evaporator and super-heater. studied refrigeration cycle is compression refrigeration cycle of unit 132 third refineries in south pars that provide chilled water for cooling refinery equipment's. cycle will be performed by ...

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 ...

Abstract In this paper, multi-objective optimization (MOO) of Al2O3-water nanofluid flow in microchannel heat sinks (MCHS) with triangular ribs is performed using Computational Fluid Dynamics (CFD) techniques and Non-dominated Sorting Genetic Algorithms (NSGA II). At first, nanofluid flow is solved numerically in various MCHS with triangular ribs using CFD techniques. Finally, the CFD data will...

Abstract In this paper, a fuzzy PID with new structure is proposed to solve the load frequency control in interconnected power systems. in this study, a new structure and effective of the fuzzy PID-type Load frequency control (LFC) is proposed to solve the load frequency control in interconnected power systems. The main objective is to eliminate the deviations in the frequency of different area...

the vehicle driving comfort has become one of the important factors of vehicle quality and receives increasing attention. in this paper, optimal points of vehicle suspension parameters are generated using modified non-dominated sorting genetic algorithm (nsga-ii) for pareto optimization of 5-degree of freedom vehicle vibration model considering three conflicting functions simultaneously. in thi...

In this paper, we present a new algorithm — an Enhanced Annealing Genetic Algorithm for Multi-Objective Optimization problems (MOPs). The algorithm tackles the MOPs by a new quantitative measurement of the Pareto front coverage quality — Coverage Quotient. We then correspondingly design an energy function, a fitness function and a hybridization framework, and manage to achieve both satisfactory...

Decomposition-based algorithms for multi-objective optimization problems have increased in popularity in the past decade. Although their convergence to the Pareto optimal front (PF) is in several instances superior to that of Pareto-based algorithms, the problem of selecting a way to distribute or guide these solutions in a high-dimensional space has not been explored. In this work, we introduc...