A Percentile Methodology Applied to Binarization of Swarm Intelligence Metaheuristics

Paola Moraga,Matias Valenzuela,Hernan Pinto,Gabriel Villavicencio,Francisco Altimiras

doi:10.29333/jisem/6348

Abstract

The binarization mechanisms of continuous metaheuristics are of interest in operational research. This is mainly due to the fact that there are a lot of combinatorial problems that are NP-hard. In this article, we exploit the concept of percentile as a mechanism of binarization of swarm intelligence continuous metaheuristics. To evaluate the behavior of our binary operator, the Multi-verse metaheuristic is used and applied to solve the combinatorial problem of the knapsack. The binary algorithm obtained, the binary multi-verse Optimizer (BMVO) shows good performance in solving the most difficult problems of the knapsack.

Highlights

In the industry, optimization problems are relevant, at the level of decision making
Performing a small state of the art of multidimensional knapsack (MKP), we find that this has been addressed in Haddar et al (2016) using a quantum binarization technique, in García et al (2018b) they applied the technique of grouping k-means to perform binarization, an improved optimization of The fruit fly in Meng and Pan (2017), in Liu et al (2016) a differential algorithm with transfer functions was used, and in Bansal and Deep (2012) a modification of the PSO equations was used
A general binarization technique which use the percentile concept is used to perform the binarization of the multiverse optimizer (MVO) algorithm

Summary

Introduction

Optimization problems are relevant, at the level of decision making. We can find binary space problems in Civil Engineering, Bio-Informatics (Barman and Kwon, 2017), Operational Research (Crawford et al, 2017, September; 2018; Garcia and Măntoiu, 2014; García et al, 2019a), resource allocation (Astorga et al, 2018; García et al, 2017, September, 2019b; Valenzuela et al, 2019, June) scheduling problems (García et al, 2017, February, 2018a), routing problems among others Another line of research that has had an important impact is the design of algorithms inspired by natural phenomena to solve optimization problems. It is a challenge to transform a continuous algorithm into its binary version without altering the exploration and exploitation processes characteristic of each metaheuristic and that subsequently it adequately performs in combinatorial problems

Objectives

Results

Conclusion