Sports inspired metaheuristics — Probably not what you think
Optimization is defined as an act, process, or methodology of making something (such as a design, system, or decision) as fully perfect, functional, or effective as possible specifically : the mathematical procedures (such as finding the maximum of a function) involved in this., by Merriam-Webster dictionary.
From this definition -or from real life- we know that it is not as simple as to achieve perfection or most effective act or process in every situation. That’s where heuristics and metaheuristics get involved. Simply, they are used for finding relatively good solutions, when it is not possible to find the optimal one. In computer science and mathematical optimization, metaheuristics are commonly used. Inspiration or impression source of the metaheuristics differs, such as behaviors of animals, natural events, biological systems and physical systems and it is used for a major categorization of metaheuristics. As it can be seen from the sample categories, most of them are inspired by the movements in a certain order in nature. This is the point where sports inspired metaheuristics differ from the others. In this article, you will find some algorithms inspired by different sports in the literature.
- Tiki — Taka Algorithm
Tiki taka is a Spanish style of play in football characterised by short passing and movement, working the ball through various channels and maintaining possession. This style of play was introduced by Johan Cruyff, a Dutch football legend, however, it has become popular with Barcelona, a Spanish club and their head coach Pep Guardiola.
From the sports side of this tactical play, it depends on the comprehensive understanding in the geometry of space on a football field of the team. A few smart football player leads the team tactically, defenders are patient and feeds the midfielders with safer and vertical passes. Ball movements are between closer players in the field, players will form a triangle of three players who will keep passing the ball among them.If the opponents enter the triangle, players will form another triangle by finding a better space.
As a computer algorithm, Tiki-Taka is designed based on the “short pass” strategy. Each player corresponds to a solution, and players will pass the ball to the nearby player, which corresponds to a neighbor solution. The player will then find a better position in accordance with the ball and key player positions. In the TTA, the concept of multiple key players (leaders) is adopted, similar to the real tiki-taka strategy. The aim of multiple leaders is to enhance solution divergence and avoid algorithm trapping in the local optimum.
2. Volleyball Premier League Algorithm
Volleyball is a team sport in which two teams of six players are separated by a net. Each team tries to score points by grounding a ball on the other team’s court under organized rules. Teams are managed by a head-coach, and have a starting lineup of 6 players, which is submitted to the referee of the games. Game area is divided into to two sub-areas by a line; originally three players are assigned to the front-row and remaining ones are staying in the back. This arrangement may be change during the game, with respect to the game rules.
Volleyball Premier League Algorithm is defined based on a volleyball team. Algorithm is divided into two parts, as active and passive, which of them are managed by the team leader. Active part depends on team formation, that changes through the match, in real life. On the other hand, passive part includes substitutions. Algorithm starts with an initial solution, is equal to a team, consist of a solution set. During the league, algorithm tries to find the best team, through the matches with opponent teams. Algorithm does not only consider the single team in the league, it eliminates the worst teams and executes transfers between the teams. At the end of the multiple seasons, algorithm stops and gives the best team (solution set) as a result. Algorithm depends on many strategies including scheduling, information sharing, repositioning, transfers etc.
3. Most Valuable Player Algorithm
In sports, a most valuable player (MVP) award is an honor typically bestowed upon an individual as the most performing player (or players) in an entire league, for a particular competition, or on a specific team. This definition is used in different sports and leagues as (W)NBA, NFL, Euroleague, FIVB etc. with different evaluation methods.
MVP algorithm is based on a population, which has a group of players that have skills. Algorithm starts with a player population, and these players are randomly distributed to teams. Teams with different skilled players compete with each other with the aim of winning games and during these matches, players try to increase their skills using this competitions.
4. Billiards Inspired Optimization Algorithm
Billiard sports are a wide variety of games of skill generally played with a cue stick, which is used to strike billiard balls and thereby cause them to move around a cloth-covered billiards table bounded by elastic bumpers known as cushions. Players try to get points by different shot strategies or throwing the balls into the holes (called pockets) in the billiard tables. This motion is provided with the shots from cue balls to ordinary balls.
Differs from the algorithms above, Billiards Inspired Optimization Algorithm consists on the mechanics of the game, since it is not a player-based game or a team sports. Each solution candidate, which contains a number of decision variables, is considered as a multi-dimensional billiards ball. Balls are represented as the agents of the optimization problem. Initialization is made through randomly distributed balls generation; and some of the best ones are selected as pockets, and divided into ordinary balls and cue balls. After initialization step, each cue balls hits target balls with the objective of moving towards the pocket.
5. World Cup Optimization Algorithm
The FIFA World Cup, often simply called the World Cup, is an international association football competition contested by the senior men’s national team of the members of the Fédération Internationale de Football Association (FIFA), the sport’s global governing body. The tournament has been performed every four years, with elimination phases distributed around continents and up to a couple of years. 32 teams compete within different rounds as round robin in group format and elimination based; their aim is to reach the World Cup, and become the greatest team of the world for 4 years, with collecting points for the FIFA World football ranking. Tournament consist on football rules with respect to the special tournament characteristics.
World Cup Optimization algorithm is a search and optimization algorithm. Teams, which represent the solutions, that attend the tournament are classified into groups by their strengths and plays with each other to get points. After round robin, some teams are eliminated and rest of the teams compete each other to reach to cup by elimination. After finding the greatest team, algorithm updates the team points up to the next tournament, then starts a new tournament until a stopping criteria is reached.
There are other interesting and well-performed sports-inspired metaheuristics and this area seems to get attention from different engineering disciplines. Some of these algorithms outperform the well-known nature based metaheuristics and are published with computational works in outstanding journals. One of the advantages of these algorithm is that they are easy to understand, if you have a slight interest in sports. In addition, sports-inspired metaheuristics (socio-inspired metaheuristics in general) seems to be a great opportunity for interdisciplinary works, to solve complex and present problems with different perspectives.
: Rashid, M. F. F. A. (2020). Tiki-taka algorithm: a novel metaheuristic inspired by football playing style. Engineering Computations.
: Moghdani, R., & Salimifard, K. (2018). Volleyball premier league algorithm. Applied Soft Computing, 64, 161–185.
: Bouchekara, H. R. E. H. (2020). Most Valuable Player Algorithm: a novel optimization algorithm inspired from sport. Operational Research, 20(1), 139–195.
: Kaveh, A., Khanzadi, M., & Moghaddam, M. R. (2020, October). Billiards-inspired optimization algorithm; a new meta-heuristic method. In Structures (Vol. 27, pp. 1722–1739). Elsevier.
: Razmjooy, N., Khalilpour, M., & Ramezani, M. (2016). A new meta-heuristic optimization algorithm inspired by FIFA world cup competitions: theory and its application in PID designing for AVR system. Journal of Control, Automation and Electrical Systems, 27(4), 419–440.
: Alatas, B. (2019). Sports inspired computational intelligence algorithms for global optimization. Artificial Intelligence Review, 52(3), 1579–1627.