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Design and modeling of a crowdsource-enabled system for urban parcel relay and delivery

機譯：支持眾包的城市包裹中轉(zhuǎn)和配送系統(tǒng)的設(shè)計與建模

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This paper proposes a crowdsource-enabled system for urban parcel relay and delivery. We consider cyclists and pedestrians as crowdsources who are close to customers and interested in relaying parcels with a truck carrier and undertaking jobs for the last-leg parcel delivery and the first-leg parcel pickup. The crowdsources express their interests in doing so by submitting bids to the truck carrier. The truck carrier then selects bids and coordinates crowdsources' last-leg delivery (first-leg pickup) with its truck operations. The truck carrier's problem is formulated as a mixed integer non-linear program which simultaneously i) selects crowdsources to complete the last-leg delivery (first-leg pickup) between customers and selected points for crowdsource-truck relay; and ii) determines the relay points and truck routes and schedule. To solve the truck carrier problem, we first decompose the problem into a winner determination problem and a simultaneous pickup and delivery problem with soft time windows, and propose a Tabu Search based algorithm to iteratively solve the two subproblems. Numerical results show that this solution approach is able to yield close-to-optimum solutions with much less time than using off-the-shelf solvers. By adopting this new system, truck vehicle miles traveled (VMT) and total cost can be reduced compared to pure-truck delivery. The advantage of the system over pure-truck delivery is sensitive to factors such as penalty for servicing outside customers' desired time windows, truck unit operating cost, time value of crowdsources, and the crowdsource mode. (C) 2017 Elsevier Ltd. All rights reserved.
機譯：本文提出了一種支持眾包的城市包裹中繼和遞送系統(tǒng)。我們認為騎自行車的人和行人是接近客戶的人群，他們有興趣與卡車承運人交換包裹，并從事最后一段包裹的交付和第一段包裹的提取工作。眾包商通過向卡車運輸商投標來表達自己的興趣。然后，卡車承運人選擇出價，并與卡車運營協(xié)調(diào)眾籌的最后一站交付（第一站取貨）?？ㄜ嚦羞\人的問題被表述為混合整數(shù)非線性程序，該程序同時進行：i）選擇眾包以完成客戶和眾包卡車中繼的選定點之間的最后一站交付（首站取貨）； ii）確定中轉(zhuǎn)站，卡車路線和時間表。為了解決卡車承運人的問題，我們首先將問題分解為優(yōu)勝者確定問題和帶有軟時間窗的同時取貨和交付問題，然后提出一種基于禁忌搜索的算法來迭代解決這兩個子問題。數(shù)值結(jié)果表明，這種解決方案方法能夠以比使用現(xiàn)成的求解器更少的時間生成接近最佳的解決方案。通過采用這種新系統(tǒng)，與純卡車交付相比，卡車的行駛里程（VMT）和總成本得以降低。與純卡車運輸相比，該系統(tǒng)的優(yōu)勢對以下因素敏感：服務(wù)外部客戶所需的時間窗口，卡車單位的運營成本，眾包的時間價值和眾包模式的維修費用。 （C）2017 Elsevier Ltd.保留所有權(quán)利。

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