Highlights Study the urban delivery problem considering uncertain assembly time. Formulate the problem to a chance-constrained programming problem. An algorithm consisting of two sub-heuristics is proposed to solve the problem. Comprehensive numerical experiments with real dataset are performed.
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.
Minimizing the total completion time of an urban delivery problem with uncertain assembly time
2019-11-03
20 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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