Reference Point Based TR-PSO for Multi-Objective Environmental/Economic Dispatch

El‐Sawy, A. A.; Hendawy, Z. M.; El-Shorbagy, M. A.

doi:10.4236/am.2013.45110

Cited by 8 publications

(5 citation statements)

References 36 publications

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“…In addition, the hybrid algorithms have also been developed and applied to a variety of MOPs and their application such as [31][32][33][34][35][36]. Hybrid algorithms can be more efficient than the basic versions of the basic approaches, because of the fact that the hybrid algorithm benefits from all the advantages of the basic algorithms.…”

Section: Different Conventional Algorithms Have Been Developed To Solvementioning

confidence: 99%

A New Hybrid Metaheuristic Algorithm for Multiobjective Optimization Problems

Farag¹,

El-Shorbagy²,

Mousa³

et al. 2020

IJCIS

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The elitist nondominated sorting genetic algorithm (NSGA-II) is hybridized with the sine-cosine algorithm (SCA) in this paper to solve multiobjective optimization problems. The proposed hybrid algorithm is named nondominated sorting sine-cosine genetic algorithm (NS-SCGA). The main idea of this algorithm is the following: NS-SCGA integrates the merits of exploitation capability of NSGA-II and exploration capability of SCA for a better search ability and speeds up the searching process. The performance of NS-SCGA is tested on the set of benchmark functions provided for CEC09. The NS-SCGA results are compared with other recently developed multiobjective algorithms in terms of convergence, spacing, and spread of the obtained nondominated solutions to the true Pareto front. The statistical analysis of the results obtained is performed by nonparametric Friedman and Wilcoxon signed-rank tests. The results prove that NS-SCGA is superior to or competitive with other multiobjective optimization algorithms considered in the comparison. Furthermore, the economic emission dispatch problem (EEDP) is solved by NS-SCGA. The operating cost (fuel cost) and pollutant emission of the standard IEEE 30-bus network with six generating units are minimized simultaneously by the NS-SCGA considering the losses. The results show the superiority of NS-SCGA and confirm its ability in solving EEDP. Finally, TOPSIS technique is applied to choose the best compromise solution from the obtained Pareto-optimal solutions of EEDP according to the decision-maker's preference.

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Section: Different Conventional Algorithms Have Been Developed To Solvementioning

confidence: 99%

A New Hybrid Metaheuristic Algorithm for Multiobjective Optimization Problems

Farag¹,

El-Shorbagy²,

Mousa³

et al. 2020

IJCIS

View full text Add to dashboard Cite

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“…Most of the engineering optimization problems have a complex search space and generally finding a continuous and differentiable objective function for this class of problems is very difficult or mostly unattainable [1]. So, applying the gradient-based optimization methods which require the continuous (or at least partially continuous) objective function(s) and its different order gradients mostly is very challenging or even impossible in some cases [2][3][4][5]. Consequently, alternative optimization tool is required for such a complex problem.…”

Section: Introductionmentioning

confidence: 99%

Effect of fuzzy-membership function types on the search capability of interactive search algorithm

Mortazavi¹

2019

JSEAM

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Fuzzy logic is widely used as the fundamental platform for the many artificial intelligence-based systems like control of subways, air conditioners, transmission systems, facial pattern recognition, antiskid braking systems. In the theory of fuzzy set, membership functions (MFs) provide an infrastructure for determining the degree of truth in a fuzzy model. So, they can play important role in the performance of these logical mechanisms. Different types of MF can be defined to fuzzification-defuzzification process (i.e. converting Boolean input to a fuzzy output and vise-versa). They are categorized and named based on the shape of their diagrams as triangular, Gaussian, trapezoidal and so forth. In the current study the effect of MF's type on the search capability of Interactive Search Algorithm (ISA) is assessed. To meet this aim, a metaheuristic technique that are known as Interactive Search Algorithm and strengthen with fuzzy adjustment mechanism is tested on solving a number of benchmark problems involving different types of MFs. The results indicate that due to stochastic essence of metaheuristic approaches the type of MF does not seriously affect the search capability of this technique. Therefore, it can be stated that the MFs should be selected based on the simplicity criterion. In other words, the simplest MF which provides the designers requirements can be the best choice.

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“…Contemporary Stochastic Search Algorithms such as PSO used by El-Sawy et al in [6], Vlachogiannis et al in [7], Selvakumar et al in [8], Park et al in [9], Sreenivasan et al in [10], Shahinzadeh et al in [11]; GA used by Damousis et al in [12], Walters et al in [13], Nanda et al in [14]; Direct Search used by Chen et al in [15] and Differential Evolution used by Balamurugan et al in [16], Noman et al in [17]; Simulated Annealing used by Vishwakarma et al in [18], Basu et al in [19]; Gravitational Search used by Mondal et al in [20], Hota et al in [21]; Cuckoo Search used by Tran et al in [22], Sekhar et al in [23]; Binary successive approximation-based evolutionary search used by Dhillon et al in [24], Mallikarjuna et al in [25] have been applied for solving the ELD problem. However, the above-mentioned optimization techniques in literature are also accompanying with their own limitations such as local optimal solution and requirement of common controlling parameters like population size, executions of many repeated stages, execution speed etc.…”

Section: Introduction He Objective Of the Economic Dispatch Problementioning

confidence: 99%

Emission Constrained Optimal Allocation of Generation using AWDO Technique.

Banerjee¹,

Sarkar²

2019

ijsgset

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The current work introduces a meta-heuristic solution of an emission constrained optimal generation scheduling problem on the Distributed Energy Resources (DERs). The Combined Economic Emission Dispatch (CEED) problem reflects the environmental effects from the gaseous pollutants from fossil-fueled power generating plants. The CEED is a method for scheduling the generation considering both emission and generation cost meeting the needs of satisfying all operational constraints and load demand as well. The CEED problem has been formulated as a multi-objective problem and that later has been converted into a single objective function using price penalty factor. A comparatively new meta-heuristic nature-inspired global optimization method, Adaptive Wind Driven Optimization (AWDO), has been proposed to solve the CEED problem solution. The key objective is to solve the CEED problem with the proposed algorithm and analyze its effectiveness of with the help of the simulation results which later have been compared with other existing algorithms for two test systems (10 thermal units and 40 thermal units) and AWDO has proved to be the best and most powerful amongst them.

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Reference Point Based TR-PSO for Multi-Objective Environmental/Economic Dispatch

Cited by 8 publications

References 36 publications

A New Hybrid Metaheuristic Algorithm for Multiobjective Optimization Problems

A New Hybrid Metaheuristic Algorithm for Multiobjective Optimization Problems

Effect of fuzzy-membership function types on the search capability of interactive search algorithm

Emission Constrained Optimal Allocation of Generation using AWDO Technique.

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