運動排程問題在這篇研究中被定義成路徑規劃問題，利用啟發式演算法建構有效率且符合賽制之賽程表。我們並以美國職棒大聯盟賽程表排程為例，收集相關文獻後，對此個案進行資料蒐集且深入研究，建立賽程表排程路徑規劃模式，期望所產出之賽程表能降低整個球季間球隊的總移動距離，及減低因球隊間移動距離差異過大造成賽程的公平性問題。 本研究以美國職棒大聯盟2009年至2011年賽程表作為比較實例，包含30個球隊一年共2430場賽事的安排，總求解時間約為4.2小時。產出之賽程表比美國職棒大聯盟近三年球季的平均總移動距離減少了約14.7萬公里，當中有23支球隊降低了每年的移動距離。此外，我們成功地降低移動距離最長與最短的球隊之間的差距達36%，減少了移動距離差異過大之不公平的問題，我們期望此系統可作為美國職棒大聯盟賽程安排之決策支援系統，將來亦可擴展應用範圍至世界各國職業運動賽程排程規劃與決策。 The scope of this study is on planning an optimal schedule for professional sports game. We take the MLB as an example to construct an effective schedule by a heuristic algorithm which meets the league rules. After collecting the references, we proceed to gather the information and to research it deeply for this case. We design the pattern for planning the schedules, and organize the related statistic reports about the scheduling. Finally, we estimate the results and analyze the targets. We expect to reduce the total moving distance of the MLB and make the schedule of the MLB fairer. This research applies the contests scheduling of year 2009 to 2011 of the MLB as a case study. It takes 4.2 hours to get the solution. The output of our system is shorter than the average moving distance of the MLB in recent 3 years by 147,000 km, and 23 out of the 30 teams can reduce their moving distances in the season. Moreover, the ratio between the two teams with the longest moving distance to the shortest moving distance is reduced by 36 %. That is, our approach makes the schedule fairer. We expect that this research can be used to establish the schedule decision support system for the MLB, and for other professional sports games around the world.