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Moth flame optimization algorithm based on decomposition for placement of relay nodes in WSNs

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Abstract

Metaheuristic algorithms have popularly been used to solve a wide range of complex engineering optimization problems. In order to solve the problems with two or more objectives multi-objective algorithms (MOAs) are used. Application of MOAs to solve multiple conflicting objectives yields a Pareto-optimal solution set. In this paper, we propose a multi-objective decomposition-based moth flame optimization (MOMFO/D) algorithm, that decomposes the objectives into multiple single objectives which are optimized simultaneously. The algorithm is used to solve the relay node placement problem, that is modeled as a bi-objective problem with the goal of minimization of average intra-cluster distance and average hop-count to improve the network lifetime. The Pareto-optimal fronts obtained through the simulations are evaluated using three distinct quality indicators namely the Inverted Generational Distance, Spacing Metric and Maximum Spread in order to evaluate the performance. The obtained results considered over a number of runs are compared with other existing optimizers in the literature such as multi-objective non-dominated sorted moth flame optimizer, and multi-objective evolutionary algorithm based on decomposition. The results demonstrate the superiority in the performance of the proposed algorithm over others. The statistical analysis of the experimental work has been carried out by conducting Friedman’s and Quade test.

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  1. Department of Computer Science and Engineering, National Institute of Technology Goa, Goa, India

    Saunhita Sapre & S. Mini

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  1. Saunhita Sapre
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Correspondence to Saunhita Sapre.

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Sapre, S., Mini, S. Moth flame optimization algorithm based on decomposition for placement of relay nodes in WSNs. Wireless Netw 26, 1473–1492 (2020). https://doi.org/10.1007/s11276-019-02213-1

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