NBA体育比赛调度问题及基于ga的求解器

Feng-Cheng Yang
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引用次数: 1

摘要

讨论了美国职业篮球协会(NBA)的比赛调度规则,并将其调度表述为一个复杂的巡回赛问题,称为NBA调度问题(NBASP)。该问题的基准测试从以前的官方时间表中描述,并组织为研究人员格式化的文件。虽然减少旅行长度是问题的目标,但评估指标:连续游戏、5天内4场游戏和周末游戏的数量都在基准中报告。提出了一种基于遗传算法的NBASP求解方法,该方法设计了专用的编码方案和解码过程,以获得可行的调度。在模拟最优解的遗传进化过程中,采用量身定制的种群初始化过程来减少不可行的初始解,并采用成本估计的启发式突变操作来有效地加速优调度的生成。在测试中使用了2014-2015年NBA赛程的基准,结果显示旅行长度减少了14%。此外,球员的不可取指标也有所减少。
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NBA Sports Game Scheduling Problem and GA-Based Solver
The game scheduling regulations of the National Basketball Association (NBA) are discussed and scheduling for it is formulated as a complex traveling tournament problem and referred to as the NBA scheduling problem (NBASP). Benchmarks for the problem were depicted from previous official schedules and organized as formatted files for researchers. Although, reducing the travel length is the goal of the problem, valuation indices: counts of back-to-back games, four-games-in-five-days, and weekend games were reported in the benchmark. A genetic algorithm (GA)-based method is proposed for solving the NBASP, in which a dedicated encoding scheme and decoding procedure were designed to obtain feasible schedules. A tailored population initialization procedure was used to reduce infeasible initial solutions and cost-estimated heuristic mutation operation was employed to effectively accelerate the generation of superior schedules in the simulated genetic evolution of an optimum solution. The 2014-2015 benchmarks of the NBA schedule was used in testing and results showed a reduction the travel length by up to 14%. Moreover, the non-preferable indices for players were also reduced.
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