An Improved Approximation Algorithm for the Traveling Tournament Problem with Maximum Trip Length Two

The Traveling Tournament Problem is a complex combinatorial optimization problem in tournament timetabling, which asks a schedule of home/away games meeting specific feasibility requirements, while also minimizing the total distance traveled by all the n teams (n is even). Despite intensive algorithmic research on this problem over the last decade, most instances with more than 10 teams in well-known benchmarks are still unsolved. In this paper, we give a practical approximation algorithm for the problem with constraints such that at most two consecutive home games or away games are allowed. Our algorithm, that generates feasible schedules based on minimum perfect matchings in the underlying graph, not only improves the previous approximation ratio from (1+16/n) to about (1+4/n) but also has very good experimental performances. By applying our schedules on known benchmark sets, we can beat all previously-known results of instances with n being a multiple of 4 by 3% to 10%

Round-robin tournaments with homogeneous rounds

We study single and double round-robin tournaments for n teams, where in each round a fixed number (g) of teams is present and each team present plays a fixed number (m) of matches in this round. In a single, respectively double, round-robin tournament each pair of teams play one, respectively two, matches. In the latter case the two matches should be played in different rounds. We give necessary combinatorial conditions on the triples (n,g,m) for which such round-robin tournaments can exist, and discuss three general construction methods that concern the cases m=1, m=2 and m=g−1. For n≤20 these cases cover 149 of all 173 non-trivial cases that satisfy the necessary conditions. In 147 of these 149 cases a tournament can be constructed. For the remaining 24 cases the tournament does not exist in 2 cases, and is constructed in all other cases. Finally we consider the spreading of rounds for teams, and give some examples where well-spreading is either possible or impossible

An Improved Scheduling Algorithm for Traveling Tournament Problem with Maximum Trip Length Two

The Traveling Tournament Problem(TTP) is a combinatorial optimization problem where we have to give a scheduling algorithm which minimizes the total distance traveled by all the participating teams of a double round-robin tournament maintaining given constraints. Most of the instances of this problem with more than ten teams are still unsolved. By definition of the problem the number of teams participating has to be even. There are different variants of this problem depending on the constraints. In this problem, we consider the case where number of teams is a multiple of four and a team can not play more than two consecutive home or away matches. Our scheduling algorithm gives better result than the existing best result for number of teams less or equal to 32

A 55-approximation Algorithm for the Traveling Tournament Problem

The Traveling Tournament Problem (TTP-$k$) is a well-known benchmark problem in tournament timetabling, which asks us to design a double round-robin schedule such that the total traveling distance of all $n$ teams is minimized under the constraints that each pair of teams plays one game in each other's home venue, and each team plays at most $k$-consecutive home games or away games. Westphal and Noparlik (Ann. Oper. Res. 218(1):347-360, 2014) claimed a $5.875$-approximation algorithm for all $k\geq 4$ and $n\geq 6$. However, there were both flaws in the construction of the schedule and in the analysis. In this paper, we show that there is a $5$-approximation algorithm for all $k$ and $n$. Furthermore, if $k \geq n/2$, the approximation ratio can be improved to $4$

A Cooperative Local Search Method for Solving the Traveling Tournament Problem

Constrained optimization is the process of optimizing a certain objective function subject to a set of constraints. The goal is not necessarily to find the global optimum. We try to explore the search space more efficiently in order to find a good approximate solution. The obtained solution should verify the hard constraints that are required to be satisfied. In this paper, we propose a cooperative search method that handles optimality and feasibility separately. We take the traveling tournament problem (TTP) as a case study to show the applicability of the proposed idea. TTP is the problem of scheduling a double round-robin tournament that satisfies a set of related constraints and minimizes the total distance traveled by the teams. The proposed method for TTP consists of two main steps. In the first step, we ignore the optimization criterion. We reduce the search only to feasible solutions satisfying the problem's constraints. For this purpose, we use constraints programming model to ensure the feasibility of solutions. In the second step, we propose a stochastic local search method to handle the optimization criterion and find a good approximate solution that verifies the hard constraints. The overall method is evaluated on benchmarks and compared with other well-known techniques for TTP. The computational results are promising and show the effectiveness of the proposed idea for TTP

ON THE BREAK INTERVAL SEQUENCES OF EQUITABLE ROUND-ROBIN TOURNAMENTS

We study the mathematical structure of equitable round-robin tournamentswith home-away assignments, and give some necessary conditions forthe feasibility of home-away tables, by using their friend-enemy tables andbreak interval sequences. We examine the relation of these conditions andenumerate the feasible break interval sequences. By our method, makingschedules of equitable round-robin tournaments can be reduced to determiningsome sequences of positive integers satisfying certain inequalities

On the application of graph colouring techniques in round-robin sports scheduling

The purpose of this paper is twofold. First, it explores the issue of producing valid, compact round-robin sports schedules by considering the problem as one of graph colouring. Using this model, which can also be extended to incorporate additional constraints, the difficulty of such problems is then gauged by considering the performance of a number of different graph colouring algorithms. Second, neighbourhood operators are then proposed that can be derived from the underlying graph colouring model and, in an example application, we show how these operators can be used in conjunction with multi-objective optimisation techniques to produce high-quality solutions to a real-world sports league scheduling problem encountered at the Welsh Rugby Union in Cardiff, Wales

ON EQUITABLE ROUND-ROBIN TOURNAMENTS WITH MAXIMAL BREAK INTERVAL GREATER THAN OR EQUAL TO 5

In our earlier paper, we studied the mathematical structure of equitable round-robin tournaments with home-away assignments, and gave some necessary conditions for their feasibility in terms of friend-enemy tables and break interval sequences. We also enumerated all the feasible home-away tables of such tournaments satisfying both the opening and the closing conditions, up to 26 teams.In this paper, we study the maximal break interval of such tournaments. From this point of view, the tournaments satisfying both the opening and the closing conditions correspond to the case where the maximal break interval is greater than or equal to 4. The aim of this paper is to examine the case where the maximal break interval is greater than or equal to 5. We enumerate all the feasible cyclic break interval sequences of such tournaments, up to 42 teams

Solving Challenging Real-World Scheduling Problems

This work contains a series of studies on the optimization of three real-world scheduling problems, school timetabling, sports scheduling and staff scheduling. These challenging problems are solved to customer satisfaction using the proposed PEAST algorithm. The customer satisfaction refers to the fact that implementations of the algorithm are in industry use. The PEAST algorithm is a product of long-term research and development. The first version of it was introduced in 1998. This thesis is a result of a five-year development of the algorithm. One of the most valuable characteristics of the algorithm has proven to be the ability to solve a wide range of scheduling problems. It is likely that it can be tuned to tackle also a range of other combinatorial problems. The algorithm uses features from numerous different metaheuristics which is the main reason for its success. In addition, the implementation of the algorithm is fast enough for real-world use.Siirretty Doriast