Scheduling the Italian National Volleyball Tournament

Cocchi, Guido; Galligari, Alessandro; Nicolino, Federica Picca; Piccialli, Veronica; Schoen, Fabio; Sciandrone, Marco

doi:10.1287/inte.2017.0932

Cited by 17 publications

(6 citation statements)

References 8 publications

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“…Naturally, in many of these some similarities to our two problem formulations can be found. Without being near to a complete list, we like to mention the following publications in this context (in chronological order): [41], [22], [36], [46], [18], [38], [37], [34], [40], [2], [24], [21], [15], [10], [47], and [20]. We also like to mention that differennt contraint programming and SAT techniques may work well in some cases, as it is suggested in papers like [45] or [5].…”

Section: Quadratic and Linear Programs For The Sailing League Problemmentioning

confidence: 99%

Sailing league problems

Schüler,

Schürmann

2024

J of Combinatorial Designs

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We describe a class of combinatorial design problems which typically occur in professional sailing league competitions. We discuss connections to resolvable block designs and equitable coverings and to scheduling problems in operations research. We in particular give suitable boolean quadratic and integer linear optimization problem formulations, as well as further heuristics and restrictions, that can be used to solve sailing league problems in practice. We apply those techniques to three case studies obtained from real sailing leagues and compare the results with previously used tournament plans.

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Section: Quadratic and Linear Programs For The Sailing League Problemmentioning

confidence: 99%

Sailing league problems

Schüler,

Schürmann

2024

J of Combinatorial Designs

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“…For a comprehensive survey on round-robin implementations for scheduling tasks, please refer to [1]. For more information on the problem's specification and solving please refer to [23][24][25][26][27][28].…”

Section: Time-constrained Double Round-robin Tournaments Itc2021mentioning

confidence: 99%

An Enhanced Particle Swarm Optimization for ITC2021 Sports Timetabling

Alsmadi¹,

Jaradat²,

Alzaqebah³

et al. 2022

Computers, Materials &Amp; Continua

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Timetabling problem is among the most difficult operational tasks and is an important step in raising industrial productivity, capability, and capacity. Such tasks are usually tackled using metaheuristics techniques that provide an intelligent way of suggesting solutions or decision-making. Swarm intelligence techniques including Particle Swarm Optimization (PSO) have proved to be effective examples. Different recent experiments showed that the PSO algorithm is reliable for timetabling in many applications such as educational and personnel timetabling, machine scheduling, etc. However, having an optimal solution is extremely challenging but having a sub-optimal solution using heuristics or metaheuristics is guaranteed. This research paper seeks the enhancement of the PSO algorithm for an efficient timetabling task. This algorithm aims at generating a feasible timetable within a reasonable time. This enhanced version is a hybrid dynamic adaptive PSO algorithm that is tested on a round-robin tournament known as ITC2021 which is dedicated to sports timetabling. The competition includes several soft and hard constraints to be satisfied in order to build a feasible or sub-optimal timetable. It consists of three categories of complexities, namely early, test, and middle instances. Results showed that the proposed dynamic adaptive PSO has obtained feasible timetables for almost all of the instances. The feasibility is measured by minimizing the violation of hard constraints to zero. The performance of the dynamic adaptive PSO is evaluated by the consumed computational time to produce a solution of feasible timetable, consistency, and robustness. The dynamic adaptive PSO showed a robust and consistent performance in producing a diversity of timetables in a reasonable computational time.

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“…Finally, FA6 limits the total cost associated with the game assignments in a timetable. As an example, some competitions try to minimize the distance traveled by the fans over holiday periods (e.g., Kendall (2008); Westphal (2014); Cocchi et al (2018)). This is different from FA5 since we assume that fans of a team immediately return back to the home venue of their team.…”

Section: Fairness and Attractiveness Constraintsmentioning

confidence: 99%