隨著美食外送平台興起，外送平台使用率逐年上升，當尖峰時段時，訂單過多造成外送員無法負荷訂單數量，進一步造成消費者訂餐等候時間增加。本研究對尖峰時段訂餐消費者收取依時擁擠費，有效移轉尖峰時段訂單數量、提高非尖峰時段訂餐使用率。此外，利用最適控制理論探討尖峰時段與非尖峰時段訂餐之均衡成本，其目的是讓兩段時間之均衡成本達成均衡。
本研究目標函數為外送平台成本最小，並考量兩時段訂餐人數、外送員數量、以及尖峰時段消費者異質特性，而消費者異質特性必須考慮時間價值。模式中所有變數皆為時間之函數，因此以最適控制理論分析本研究動態問題，而不需使用複雜之成本函數之間的關係；此外，本研究將時間與兩時段訂餐人數視為縱軸以及橫軸，但亦有可能因尖峰時段訂餐人數過多而使系統均衡成本增加，而進一步對尖峰時段消費者收取動態依時擁擠費，舒緩尖峰時段訂餐數量而轉移至非尖峰時段，最終兩時段訂餐之成本將達成均衡。
本研究利用Mathematica求算尖峰時段擁擠費；考慮願付價格以及訂餐之服務費可推導尖峰時段之動態依時擁擠費。綜合上述，固可提供美食外送平台研擬動態依時擁擠費之參考，藉此讓兩訂餐時段訂餐成本達致均衡。範例分析結果顯示當時間價值α=1.4可知越接近第60分鐘時，擁擠費越高，部分尖峰時段消費者願意負擔較高擁擠費，而不願意負擔擁擠費之消費者將轉移至非尖峰時段訂餐；而當尖峰時段與非尖峰時段訂單差距較小時可得知因過多訂單轉移至非尖峰時段，導致於非尖峰時段訂單過多而使訂單等候時間隨之增加，最終導致擁擠費隨之升高。

With the rise of food delivery platforms, the utilization rate of food delivery platforms has increased year by year. During peak hours, too many orders make the delivery staff unable to process the number of orders, further increasing the waiting time for consumers to order food. In this study, consumers who order food during peak hours are charged congestion charges on time, which effectively shifts the number of orders during peak hours and improves the utilization rate of meal orders during off-peak hours. In addition, the optimal control theory is used to explore the equilibrium cost of ordering meals during peak and off-peak hours. The purpose is to achieve a balance between the equilibrium costs of the two periods.
The objective function of this research is to minimize the cost of the take-out platform, and consider the number of menus, the number of take-out staff, and the heterogeneous characteristics of consumers during peak hours. The heterogeneous characteristics of consumers must consider the value of time. All variables in the model are functions of time. Therefore, this paper adopts optimal control theory to analyze the dynamic problems of this research without using complex cost functions. In addition, this study uses time and the number of menus in the two periods as the vertical and horizontal axes, but it is also possible that the system balance cost will increase due to the excessive number of orders during peak hours, and consumers will be further charged for dynamic time during peak hours. Congestion charges to ease the number of orders during peak hours and transfer to off-peak hours, and finally two orders. The cost will be balanced.
This study uses Mathematica to calculate the congestion charge during peak hours; considering the willingness to pay and the service fee for ordering meals, the dynamic hourly congestion charge during peak hours can be derived. Based on the above, it can provide a reference for the takeaway platform to formulate a dynamic punctual congestion charge, so as to achieve a balance between the ordering costs of the two ordering periods. The example analysis results show that when the time value α=1.4, the closer to the 60th minute, the higher the congestion charge. Some consumers are willing to pay higher congestion charges during peak hours, and the consumer charges who are unwilling to pay the congestion charge will be transferred to Order food during off-peak hours; and when the order gap between peak and off-peak hours is small, it can be known that too many orders are transferred to off-peak hours, resulting in too many orders during off-peak hours, which will increase order waiting time and eventually lead to an increase in congestion charges.

摘要 I
英文摘要 II
致謝 IV
目錄 V
圖目錄 VII
表目錄 VIII
第一章 緒論 1
1.1研究背景與動機 1
1.2研究目的 2
1.3研究範圍 5
1.4研究流程 5
1.5研究方法與架構 7
第二章 文獻回顧 9
2.1擁擠收費文獻回顧 9
2.2平台經濟文獻回顧 14
2.3共享經濟文獻回顧。 15
2.4最適控制理論 16
第三章 模式建構 19
3.1問題假設 19
3.1.1消費者下訂單流程 19
3.1.2參數假設 20
3.2尖峰時段成本模式構建 21
3.2.1等候時間成本分析 22
3.2.2時程延滯成本分析 24
3.3非尖峰時段成本模式構建 25
3.3.1時程延滯成本分析 26
3.4系統目標函數構建 27
第四章 最適控制問題 28
4.1共狀態變數經濟意義分析 28
4.1.1尖峰時段經濟意義分析 29
4.1.2非尖峰時段經濟意義分析 29
4.2依時擁擠費分析 30
4.2.1尖峰時段依時擁擠費 30
第五章 範例與敏感度分析 32
5.1範例分析 32
5.2敏感度分析 34
第六章 結論與建議 38
6.1結論 38
6.2建議 38
參考文獻 40

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英文部分
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