Tennis Tournaments Planning and Scheduling

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Scheduling tournaments is a little more challenging than one might desire, in order to build a optimize structure of the matches, it is necessary to study carefully how tennis works since its behavior is not conventional or ordinary and has certain restrictions that need to be taken into account as there are no home or away games and there will be no round-robin structure but single elimination tournaments instead. 

Sports scheduling consist in determining the date, the venue in which each game of a tournament will be played and game assignment. Heuristics and hybrid methods will be used to carry out the organization of a tennis matches with the decomposition in three sub-problems: game assignment, individual elimination and court scheduling. The objective of this report is to study Scheduling and Timetabling in Tennis Tournaments to find a feasible solution depending on the number of players and facilities available (courts), as well as available days to carry out matches.

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Interest in sport has increased over the past few decades, since it helps to maintain or improve physical fitness and also provides entertainment to participants and spectators. Sports are great for so many different reasons. Most of them offer great workouts, competition, friends and fun. Tennis is a mental sport, it stimulates the mind in ways that other sports do not. The interesting about this is that a person can be a great player, but if his mental game is weak, he will never fulfill his potential. 

It is necessary to be mentally strong. That is why the uncertainty of how long a game lasts, simply, you do not know. It depends on the place, the players, the mentality of them. As it can last 2 hours it can be extended to 11 hours. How can exactly be known? How in tennis tournaments can accurately have a schedule? The following report details an analysis of how tennis tournament planning and scheduling are built and if they can be more efficient and how can they be improved.

The following statement that will be presented is what throughout this article will seek to answer and investigate. It is wanted to know how does a tournaments scheduling and planning of tennis can be improved depending the total player, how many categories are, courts and days available. It seeks to find an effective way using the factors mentioned above to know how many hours per day during a certain time are needed for the tournament to come to an end which will be following an accurate schedule.

Ramli et al (2012) describes sports tournament scheduling as the process of assigning essential activities in sequence with a certain time to complete a specific activity. This is a challenging task due to the variety of different requirements and restrictions that must follow and take into consideration. Most of the time, the inefficiency of a tournament schedule exists when they are not met.

Tennis is usually played outdoors but the first important factor that is taken into account is the weather, if it is located in a rainy location, it is required for most of the places with this type of weather indoor tennis, even though, the cost is really high due to the heating system (Della Croce et al, 1999).

In particular, it is desired that each match has an equally available time, although it is not known how long a tennis match will last. Following the Haselgrove and Leech and Schellenberg et al methods, it has been solved during the past few decades. It is called balanced tournaments designs (BTDS), essentially consists in taking the parameter to be the number n of teams, rather than 12n (Blest, D.C and Fitzgerald, D.G., 1988).

On the other hand, Alan M. Nevill et al (1997) tried to identify if there was a home advantage in international tennis and after their studies it was found that home advantage does not appear to be a factor influencing the performance of players during this type of competitions. The reason of this is the relatively objective of the scoring systems used in tennis and golf, unlike the subjective decisions of the referee on team-games . That said, home and away will not be a restriction or concern in this paper. It will be taken as if there was no home advantage. In the following subsections, the different methods, approaches and relevant information that have been used, proposed and researched will be shown in order to see which of them can be used to address the research question.

A key aspect of sporting events is the ability to generate optimal and feasible schedules and that are seen as fair to all those who have an interest in the specific sport. Previous works related to various sports tournaments scheduling problem have been identified and they used several approaches or techniques. Such as, Mathematical Programming to solve Sports League Scheduling Problem (SLSP) (McAloon et al, 1997), Simulated Annealing technique (Hentenryck et al, 2005), Constraint-based Programming (CP) technique to obtain the optimum solution or a quick and feasible solution (Nemhauser, 1997).. In addition, a hybrid technique has begun to be implemented in sport tournament scheduling as the integration of CP and Tabu Search (TS) (Costa, 1995).

This is a basic approach to problems like tournament scheduling problem. The problem is divide it into smaller subproblems and solve these. After solve the subproblems, it is used their solutions and they are merged to find the panoramic solution. Decomposition itself is a helpful technique, but to solve the sub parts, it is need to use another technique.

This is used in all sorts of problems and it is also used in tournament scheduling problems. There are a lot of techniques and some of them work better on specifics problems. The tabu search is a type of heuristic and it consists in generate an acceptable solution in a lower amount of time. First, it is going to be find a viable solution and then, it will be improved by making smart decisions. Hamiez and Hao (2001), formulate a sport scheduling problem as a constraint satisfaction problem. They started with an accepted solution and then they tried to find the best solution possible using tabu search. Then, they used a algorithm to evaluate the quality of solutions.

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