以往學術界在長途客運的排程規劃上,大都基於確定性需求,簡化現實每日營運的隨機需求現象。另外實務上,長途客運業者的短期營運目標可能同時考量最大化營運利潤與市場占有率,並非如文獻上常見之單一營運目標。因此,本研究考量多營運目標及每日隨機需求之特性,利用網路流動技巧,構建一隨機性需求下多目標城際客運排程規劃模式,以期幫助業者有效的規劃季節車隊排程與班次表。此模式可定式為一多目標非線性混合整數規劃問題,本研究利用權重法與模擬技巧,發展一多目標隨機啓發解法以求解模式。為比較確定性與隨機性需求模式,在隨機營運環境中的績效優劣,本研究亦發展一模擬評估方法。最後,本研究以國內一長途客運公司的營運資料為例,進行範例測試,結果甚佳,顯示本研究模式與求解演算法應可為實務業者之參考。
In the past, research scholars usually used deterministic passenger demands as input for inter-city bus scheduling, simplifying the stochastic disturbances of daily passenger demands in actual operations. In addition, inter-city bus carriers in practice may aim at maximizing both the operating profit and the market share in their short-term operations, instead of confining to a single objective which was usually adopted in the inter-city bus scheduling literature. Considering the multiple objective and stochastic demands in actual operations, we employed network flow techniques to construct a stochastic-demand multi-objective scheduling model, with the objectives of maximizing the operating profit and the number of passengers, to help inter-city bus carriers effectively plan their bus fleet routes and timetables in their short-term operations. The model is formulated as a multiple objective nonlinear mixed integer pro grain. We used the weighting method and the simulation technique to develop a heuristic algorithm to solve the model. To compare the performance of the deterministic-demand and stochastic-demand scheduling models in actual operations, we developed a simulation -based evaluation method. Finally, we conducted a case study using real operating data from a major Taiwan inter-city bus carrier The results indicated that the model and the solution algorithm could he useful for inter-city bus carriers.