Solving the Sports League Scheduling Problem with Tabu Search

In this paper we present a tabu approach for a version of the Sports League Scheduling Problem. The approach adopted is based on a formulation of the problem as a Constraint Satisfaction Problem (CSP). Tests were carried out on problem instances of up to 40 teams representing 780 integer variables with 780 values per variable. Experimental results show that this approach outperforms some existing methods and is one of the most promising methods for solving problems of this type

A note on a sports league scheduling problem

Sports league scheduling is a difficult task in the general case. In this short note, we report two improvements to an existing enumerative search algorithm for a NP-hard sports league scheduling problem known as "prob026" in CSPLib. These improvements are based on additional rules to constraint and accelerate the enumeration process. The proposed approach is able to find a solution (schedule) for all prob026 instances for a number T of teams ranging from 12 to 70, including several T values for which a solution is reported for the first time.Comment: 9 page

Presentation of dissertation/thesis sheduling system (PDTSS)

In this study we will concentrate on the presentation of scheduling problems in an attempt to develop a web-based, automatic presentation scheduling system which can be employed by Advanced Informatics School, Universiti teknologi Malaysia (UTM AIS). So far this matter has been carried out manually until UTM AIS. This occurs on the event that the presentation scheduling process that was being managed turns out to be rather difficult for administration. The presentation scheduling problem is related to the scheduling of number of presentations to the venues and the limited available timeslots and also allocating some examiners for every presentation while taking the need to satisfy a group of defined constraints into consideration. Furthermore, the aforementioned system enables the staff and personnel to email or print the scheduling timetable of presentation. Implementing this system in UTM AIS is influenced by a group of presentations, the overlapping of examiners has to be avoided and the presentations have to be distributed among the examiners equally and fairly also the examiners must have the minimum possible gap between the presentations which they attend in. Greedy algorithm has been employed in this report. The software development model employed for the structuring and controlling of the developmental procedure of dissertation/thesis scheduling system’s presentation is incremental development model. The system will be implemented by C# programming language. The software documentations which were conducted in accordance with DoD-2167A standards in this study consist of Software Development Plan (SDP), Interface Requirements Specification (IRS), Software Requirements Specification (SRS) and system Design Description (SDD)

Fixture-scheduling for the Australian Football League using a Multi-objective Evolutionary Algorithm

AFL football is a team sport that entertains millions and contributes a huge amount of money to the Australian economy. Scheduling games in the AFL is difficult, as a number of different, often conflicting, factors must be considered. In this paper, we propose the use of a multi-objective evolutionary algorithm for determining such a schedule. We detail the technical details needed to apply a multi-objective evolutionary algorithm to this problem and report on experiments that show the effectiveness of this approach. Comparison with actual schedules used in the AFL demonstrates that this approach could make a useful contribution

A hybrid constraint-based programming approach to design a sports tournament scheduling

We investigate the problem of sports tournament scheduling as reflected in the quality of tournament schedule in University Utara Malaysia (UUM). The background of the sports tournament problems that inefficiency of the human scheduler, time-consuming task and unfairness among the athletes that need to be solved gives direction and motivation in investigating the problem of scheduling the sports tournament. Subsequently,previous work related to the problem is discussed. Thus, we present an innovative hybrid of a constraint-based algorithm and a neighbourhood search, which is an exploration into alternative and improved methodology in the problem of sports tournament scheduling with special multiple constraints. A scheduling system is then developed. As a result, fair distribution of break or rest times and game venues among the competing teams are achieved in our objectives. The sports tournament scheduling system assists and improves the sports events management through high quality schedule as compared with the current human scheduler, which consider rest period, day and time preferences and venue availability. Thus, this sophisticated algorithm provides the feasible, optimum, efficient and quick solution

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

Fútbol strategies applied to optimize combinatortial problems to create efficent results – the soccer heuristic

Master of ScienceDepartment of Industrial & Manufacturing Systems EngineeringTodd EastonHeuristics are often implemented to find better solutions to computationally challenging problems. Heuristics use varying techniques to search for quality solutions. Several optimization heuristics have drawn inspiration from real world practices. Ant colony optimization mimics ants in search of food. Genetic algorithms emulate traits being passed from a parent to a child. Simulated annealing imitates annealing metal. This thesis presents a new variable neighborhood search optimization heuristic, fútbol Strategies applied to Optimize Combinatorial problems to Create Efficient Results, which is called the SOCCER heuristic. This heuristic mimics fútbol and the closest player to the ball performs his neighborhood search and players are assigned different neighborhoods. The SOCCER heuristic is the first application of variable neighborhood search heuristic that uses a complex structure to select neighborhoods. The SOCCER heuristic can be applied to a variety of optimization problems. This research implemented the SOCCER heuristic for job shop scheduling problems. This implementation focused on creating a quality schedule for a local limestone company. A small computational study shows that the SOCCER heuristic can quickly solve complex job shop scheduling problems with most instances finishing in under an half an hour. The optimized schedules reduced the average production time by 7.27%. This is roughly a 2 day decrease in the number of days required to produce a month’s worth of orders. Thus, the SOCCER heuristic is a new optimization tool that can aid companies and researchers find better solutions to complex problems

Solving hard industrial combinatorial problems with SAT

The topic of this thesis is the development of SAT-based techniques and tools for solving industrial combinatorial problems. First, it describes the architecture of state-of-the-art SAT and SMT Solvers based on the classical DPLL procedure. These systems can be used as black boxes for solving combinatorial problems. However, sometimes we can increase their efficiency with slight modifications of the basic algorithm. Therefore, the study and development of techniques for adjusting SAT Solvers to specific combinatorial problems is the first goal of this thesis. Namely, SAT Solvers can only deal with propositional logic. For solving general combinatorial problems, two different approaches are possible: - Reducing the complex constraints into propositional clauses. - Enriching the SAT Solver language. The first approach corresponds to encoding the constraint into SAT. The second one corresponds to using propagators, the basis for SMT Solvers. Regarding the first approach, in this document we improve the encoding of two of the most important combinatorial constraints: cardinality constraints and pseudo-Boolean constraints. After that, we present a new mixed approach, called lazy decomposition, which combines the advantages of encodings and propagators. The other part of the thesis uses these theoretical improvements in industrial combinatorial problems. We give a method for efficiently scheduling some professional sport leagues with SAT. The results are promising and show that a SAT approach is valid for these problems. However, the chaotical behavior of CDCL-based SAT Solvers due to VSIDS heuristics makes it difficult to obtain a similar solution for two similar problems. This may be inconvenient in real-world problems, since a user expects similar solutions when it makes slight modifications to the problem specification. In order to overcome this limitation, we have studied and solved the close solution problem, i.e., the problem of quickly finding a close solution when a similar problem is considered