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Non-Dominated Sorting Genetic Algorithm Based on Altruism for Solving Multi-Objective Optimization Problems

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Multiobjective optimization problems are typically complex problems. Multiobjective optimization aim to find Pareto-optimal solutions because no single unique solution is the best. We can solve multiob- jective optimization problems mathematically or by applying heuristics or metaheuristic algorithms. Metaheuristic algorithms have big advantages in dealing with multiobjective optimization problems. Revised non-dominated sorting genetic algorithm (NSGA-II) is an effective algorithm for finding pareto optimal front. In this paper, we enhanced the performance of NSGA-II for multiobjective optimization by adding altruism. Altruism here depends on gene rather than chromosome. The proposed algorithm named, the non-dominated sorting genetic algorithm with gene based altruism (NSGA-II-GBA). The proposed algorithm favored over other algorithms because of its advantages in reducing number of generations to obtain optimal solutions, time and space complexity. And also increased search diversity and convergence speed of multiobjective optimization problems. In this paper we describe the proposed algorithm for solving multiobjective optimization problems. In addition, we also validate the algorithm against a set of multiobjective test functions and two real life engineering design problems are also solved to validate the efficiency and, applicability of the proposed algorithm in solving such problems.
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Keywords: Altruism; Genes Underlying Altruism; Genetic Algorithm; Multiobjective Optimization; Revised Non-Dominated Sorting

Document Type: Research Article

Affiliations: 1: Department of Operations Research, Faculty of Computers and Informatics, Zagazig University, El-Zera Square, Zagazig, Sharqiyah, 44519, Egypt 2: Department of Operations Research, Faculty of Computers and Information, Menoufia University, Menoufia, Shebin-El-Kome, 32511, Egypt 3: Department of Computer Science, Faculty of Computers and Informatics, Zagazig University, El-Zera Square, Zagazig, Sharqiyah, 44519, Egypt

Publication date: August 1, 2016

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  • Journal of Computational and Theoretical Nanoscience is an international peer-reviewed journal with a wide-ranging coverage, consolidates research activities in all aspects of computational and theoretical nanoscience into a single reference source. This journal offers scientists and engineers peer-reviewed research papers in all aspects of computational and theoretical nanoscience and nanotechnology in chemistry, physics, materials science, engineering and biology to publish original full papers and timely state-of-the-art reviews and short communications encompassing the fundamental and applied research.
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