Minimizing the total completion time of an urban delivery problem with uncertain assembly time

Bingbing Liu, Xiaolong Guo, Yugang Yu and Qiang Zhou

Transportation Research Part E: Logistics and Transportation Review, 2019, vol. 132, issue C, 163-182

Abstract: This paper studies a stochastic programming problem to minimize the total completion time consists of the travel time and the assembly time, for a new class of urban delivery problems. The problem is formulated into a chance-constrained programming problem and the probability distribution characteristics of the uncertainty of product assembly time are obtained using a statistical learning method. Then the original chance-constrained programming problem can be converted into an equivalent deterministic programming problem. Subsequently, an algorithm consisting of two sub-heuristics is proposed to solve the deterministic problem. Finally, comprehensive numerical experiments with real dataset show the superiority of the model and the algorithm.

Keywords: Urban delivery problem; Uncertainty; Chance constraint; Solving algorithm; Real data; Statistical learning estimation (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.tre.2019.11.002

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