Abstract
The League Championship Algorithm (LCA) is sport-inspired optimization algorithm that was introduced by Ali Husseinzadeh Kashan in the year 2009. It has since drawn enormous interest among the researchers because of its potential efficiency in solving many optimization problems and real-world applications. The LCA has also shown great potentials in solving non-deterministic polynomial time (NP-complete) problems. This survey presents a brief synopsis of the LCA literatures in peer-reviewed journals, conferences and book chapters. These research articles are then categorized according to indexing in the major academic databases (Web of Science, Scopus, IEEE Xplore and the Google Scholar). The analysis was also done to explore the prospects and the challenges of the algorithm and its acceptability among researchers. This systematic categorization can be used as a basis for future studies. Keywords: Global Optimization, League Championship Algorithm, NP-Complete Problems, Sport- Inspired Algorithm, Swarm Algorithms, Optimization Algorithm
Highlights
League Championship Algorithm (LCA) is a population based algorithmic framework for global optimization over a continuous search space first proposed by Kashan[1]
A general characteristic between all population based optimization algorithms similar to the LCA is that they both try to improve a population of achievable solutions to potential areas of the search space when seeking the optimization
Optimization algorithms are dynamic research areas with rapidly increasing literatures. It is a common knowledge among researchers that combinatorial optimization problems like the travelling salesman problem are non-deterministic polynomial times (NP-hard) problems[7,8], which implies that there are no fast solutions or exact solutions for such problems
Summary
League Championship Algorithm (LCA) is a population based algorithmic framework for global optimization over a continuous search space first proposed by Kashan[1]. LCA is a newly proposed stochastic population based algorithm for continuous global optimization which tries to imitate a championship situation where synthetic football clubs participate in an artificial league for a number of weeks. This algorithm has been tested in many areas and performed creditably well as compared to other known optimization schemes or heuristics algorithms[6]. Many discrete and continues optimization problems are NP-complete, optimal solution techniques which we can execute as a polynomial time is not attainable with a very high probability These types of problems are tackled by the construction of heuristics, metaheuristics or approximation algorithms which run in polynomial time and are often the best known method to find efficient solutions[9,10]
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