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AN EVALUATION OF A CONSTRAINED MULTI-OBJECTIVE GENETIC ALGORITHM

Youssef ALIOUI, Reşat ACAR
2020 Journal of Scientific Perspectives  
The aim of this study is to evaluate the performance of a constrained version of the Nondominated Sorting Genetic Algorithm 2 (NSGA 2), a multi-objective evolutionary optimization algorithm, written in  ...  Over the last decades, evolutionary algorithms have been largely used in solving optimization problems in various fields of science.  ...  INTRODUCTION Solving multi-objective optimization problems have interested researchers in all the fields of science over the last decades.  ... 
doi:10.26900/jsp.4.011 fatcat:pstxblhv3vagdchg375k5wssra

Optimization of a sustainable closed loop supply chain network design under uncertainty using multi-objective evolutionary algorithms

E. Pourjavad, R.V. Mayorga
2018 Advances in Production Engineering & Management  
Due to NPhardness of the problem, a non-dominated sorting genetic algorithm-II (NSGA-II) is developed to solve this multi-objective mathematical model.  ...  The obtained results are validated with the non-dominated ranking genetic algorithm (NRGA), due to there is no benchmark for this problem.  ...  Non-dominated ranked genetic algorithm for solving constrained multi-objective optimization problems, Journal of Theoretical and Applied Information Technology, Vol. 5, 714-725.  ... 
doi:10.14743/apem2018.2.286 fatcat:nzjs7kiwsncqxken4kktmowahe

Non Dominated Sorting Genetic Algorithm for Chance Constrained Supplier Selection Model with Volume Discounts [chapter]

Remica Aggarwal, Ainesh Bakshi
2014 Lecture Notes in Computer Science  
A Fast Non-dominated Sorting Genetic Algorithm (NSGA-II), a variant of GA, adept at solving Multi Objective Optimization, is used to obtain the Pareto optimal solution set for its deterministic equivalent  ...  This paper proposes a Stochastic Chance-Constrained Programming Model (SCCPM) for the supplier selection problem to select best suppliers offering incremental volume discounts in a conflicting multi-objective  ...  A Fast Non-dominated Sorting Genetic Algorithm (NSGA-II) [7] , a variant of GA, adept at solving Multi Objective Optimization, is used to obtain the Pareto optimal solution set for our problem statement  ... 
doi:10.1007/978-3-319-05458-2_48 fatcat:7a74qa3cqvbtjfe2shpvt6cr5e

A novel evolutionary framework based on a family concept for solving multi-objective bilevel optimization problems

Jesús-Adolfo Mejía-de-Dios, Alejandro Rodríguez-Molina, Efrén Mezura-Montes
2022 Proceedings of the Genetic and Evolutionary Computation Conference Companion  
Multi-objective Bilevel Optimization (MOBO) problems are challenging because they include an optimization problem as part of the constraints within a multi-objective problem.  ...  The proposed framework shows competitiveness in the experiments compared to a state-of-the-art algorithm for challenging constrained MOBO problems.  ...  The Nondominated Sorting Genetic Algorithm (NSGA-II) [2] is one of the most used methods to solve multi-objective problems.  ... 
doi:10.1145/3520304.3529045 fatcat:eimcv4b4qzfc7lpju4omvazrsi

Voltage Stability Constrained Optimal Power Flow Using NSGA-II

Sandeep Panuganti, Preetha Roselyn John, Durairaj Devraj, Subhransu Sekhar Dash
2013 Computational Water Energy and Environmental Engineering  
This work includes multi-objective evolutionary algorithm techniques such as Genetic Algorithm (GA) and Non-dominated Sorting Genetic Algorithm II (NSGA-II) approach for solving Voltage Stability Constrained-Optimal  ...  Multi-Objective OPF, formulated as a multi-objective mixed integer nonlinear optimization problem, minimizes fuel cost and minimizes emission of gases, as well as improvement of voltage profile in the  ...  NSGA [4] is a popular non-domination based genetic algorithm for multi-objective optimization.  ... 
doi:10.4236/cweee.2013.21001 fatcat:v744wdguxrb7fnfnrgguitmtq4

Solution of constrained optimization problems by multi-objective genetic algorithm

V.S. Summanwar, V.K. Jayaraman, B.D. Kulkarni, H.S. Kusumakar, K. Gupta, J. Rajesh
2002 Computers and Chemical Engineering  
This paper introduces a method for constrained optimization using a modified multi-objective algorithm.  ...  A range of problems including non-linear programming and mixed integer non-linear programming has been solved to test the efficacy of the proposed algorithm.  ...  Constrained optimization by multi-objecti6e genetic algorithm: COMOGA This method is inspired by the techniques of multiobjective optimization through genetic algorithms and was proposed by Surry and  ... 
doi:10.1016/s0098-1354(02)00125-4 fatcat:pj5mel3ahbgq7ayok6c2ks7yca

Goal oriented ranking scheme

A. R. Khaparde, A. Mokhade, P. D. Dahiwale
2010 Proceedings of the International Conference and Workshop on Emerging Trends in Technology - ICWET '10  
The method is variant of multi objective real coded Genetic algorithm inspired by penalty approach. It is evaluated on eleven different single and multi objective problems found in literature.  ...  Evolutionary algorithms (EAs) have received a lot of interest in last two decade due to the ease of handling the multiple objectives.  ...  [7] , Multi objective approaches of constrained problems based on Shaffers VEGA [11] is found in [12] [10] .To directly apply a multi objective EA based on non-domination on a constrained optimization  ... 
doi:10.1145/1741906.1742019 dblp:conf/icwet/KhapardeMD10 fatcat:umkz7rhokfh3tawg7q2xmn4rqa

A New Multi-objective Sorting Algorithm And Its Combination With Game Theory For Optimizing I-beam Engineering System

Hamidreza Navidi, Mojtaba Ahmadie Khanesar, Leila Falahiazar
2015 Journal of Mathematics and Computer Science  
This paper proposed a new average non-dominated sorting genetic algorithm (NAVNSGA).  ...  The proposed NAVNSGA is improved the disadvantages of the Elitist multi-objective algorithms and Non-elitist multi-objective algorithms as possible.  ...  Proposing a New AVerage Non-dominated Sorting Genetic Algorithm A New AVerage Non-dominated Sorting Genetic Algorithm (NAVNSGA) is proposed in this paper to solve the disadvantage of NSGAI and NSGAII algorithms  ... 
doi:10.22436/jmcs.014.04.04 fatcat:fg6jjhgksfggrhhp4bn3wp43oa

Non-Dominated Sorting Moth Flame Optimizer: A Novel Multi-Objective Optimization Algorithm for Solving Engineering Design Problems

Pradeep Jangir
2018 Engineering Technology Open Access Journal  
The results are verified by comparing NSMFO against Multi objective Colliding Bodies Optimizer (MOCBO), Multi objective Particle Swarm Optimizer (MOPSO), non-dominated sorting genetic algorithm II (NSGA-II  ...  This novel article presents the multi-objective version of the recently proposed Moth-flame optimizer (MFO) known as Non-Dominated Sorting Moth Flame Optimizer (NSMFO).  ...  multi-objective algorithms Multi objective Colliding Bodies Optimizer (MOCBO) [18] , Multi objective Particle Swarm Optimizer (MOPSO) [19, 20] , Non-dominated Sorting Genetic Algorithm (NSGA) [21]  ... 
doi:10.19080/etoaj.2018.02.555579 fatcat:rtidmhdacnbwvbkacvmznefmte

Optimization of Multi-objective Job-shop Scheduling under Uncertain Environment

Cheng Wang, Lei Zeng
2019 Journal Europeen des Systemes Automatises  
After that, a genetic algorithm (GA) coupling non-dominated ranking was designed to solve the multi-objective JSP.  ...  In this paper, the multi-objective job-shop scheduling problem (JSP) is optimized based on the tradeoff between time, cost and robustness.  ...  ACKNOWLEDGMENT This work was supported by basic Scientific Research project of Department of Education of Heilongjiang Province (135109523, Multi-objective Integrated production Planning system and Optimization  ... 
doi:10.18280/jesa.520210 fatcat:fqgnvv4qzndclhxpzqdhwqoyqm

Irrigation water allocation optimization using multi-objective evolutionary algorithm (MOEA) − a review

Ibrahim Mwita Fanuel, Allen Mushi, Damian Kajunguri
2018 International Journal for Simulation and Multidisciplinary Design Optimization  
This paper analyzes more than 40 papers with a restricted area of application of Multi-Objective Genetic Algorithm, Non-Dominated Sorting Genetic Algorithm-II and Multi-Objective Differential Evolution  ...  (MODE) to solve the multi-objective problem in agricultural water management.  ...  , multi-objective evolutionary algorithms, irrigation, optimization, genetic algorithms, non-sorting genetic algorithms and differential evolution.  ... 
doi:10.1051/smdo/2018001 fatcat:hc5bsfms3ncednn25pjtngukza

Multi-objective optimization using genetic algorithms: A tutorial

Abdullah Konak, David W. Coit, Alice E. Smith
2006 Reliability Engineering & System Safety  
Multi-objective formulations are a realistic models for many complex engineering optimization problems.  ...  A reasonable solution to a multi-objective problem is to investigate a set of solutions, each of which satisfies the objectives at an acceptable level without being dominated by any other solution.  ...  Introduction The objective of this paper is present an overview and tutorial of multiple-objective optimization methods using genetic algorithms (GA).  ... 
doi:10.1016/j.ress.2005.11.018 fatcat:46bseh7efzfwnfw2g7iuv7seki

Convex hull ranking algorithm for multi-objective evolutionary algorithms

M. Davoodi Monfared, A. Mohades, J. Rezaei
2011 Scientia Iranica. International Journal of Science and Technology  
The proposed algorithm is very suitable for convex multi-objective optimization problems.  ...  Multi-Objective Optimization (MOO) algorithms.  ...  Multi-objective evolutionary algorithms A multi-objective optimization problem can be written as follows [11] : Minimize/Maximize f m (X), m = 1, 2, . . . , M.  ... 
doi:10.1016/j.scient.2011.08.017 fatcat:s4q4h535kvcexp7n6ksch4fhmi

Application of Genetic Algorithm for Solving Multi-Objective Optimization Problems in Robust Control of Distillation Column

S.Amir Ghoreishi, Mohammad Ali Nekoui, Saeed Partovi, S. Omid Basiri
2011 International Journal of Advancements in Computing Technology  
In this paper, popular adaptations of the simple GA, non-dominated sorting genetic algorithms, are used to solve robust control design problems.  ...  A genetic algorithm (GA) for the class of multi-objective optimization problems that appears in the design of robust controllers is presented in this paper.  ...  Horn, Nafpliotis and Goldberg (1994) used Pareto domination tournaments instead of non-dominated sorting and ranking selection method in solving multi-objective optimization problems.  ... 
doi:10.4156/ijact.vol3.issue1.4 fatcat:lpxptblfyzczvna43dfnb33ufm

Solving Multi-Objective Problems Using Bird Swarm Algorithm

Essam H. Houssein, Mohammed M. Ahmed, Mohamed Abd Elaziz, Ahmed A. Ewees, Rania M. Ghoniem
2021 IEEE Access  
INDEX TERMS Bird swarm algorithm, multi-objective optimization, constrained optimization problems, unconstrained optimization problems, engineering optimization problems, Pareto front, Pareto optimal solutions  ...  The MBSA obtains some of the different non-dominated techniques that maintain variety amongst the optimal solutions.  ...  [12] published the non-dominated sorting genetic algorithm (NSGA-II). Coello et al.  ... 
doi:10.1109/access.2021.3063218 fatcat:rmd36fivyvaj3odd5zomwnznjm
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