4.7 Article

An adaptive large neighborhood search for the robust rig routing

Journal

EXPERT SYSTEMS WITH APPLICATIONS
Volume 231, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2023.120626

Keywords

Logistics; Threshold robustness; Uncapacitated vehicles; Split delivery; Time windows; Metaheuristics

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In the oil and gas industry, auxiliary maintenance and storage buildings need to be constructed near exploration sites. Mobile drilling rigs travel from one site to another, drilling wells for construction. Work deviations from expected values are maximized while keeping traveling costs below a threshold. This research proposes a mathematical model and algorithm to solve the Drilling Rig Routing Problem with uncertainties.
In the oil and gas industry, there is a need for constructing auxiliary maintenance and storage buildings nearby exploration sites. As the initial stage for such constructing purposes, it is required to drill wells for construction piles. To this end, there is a fleet of mobile drilling rigs traveling from one exploration site to another, performing the work on drilling wells. For each site, we have a time window for completing all the work on drilling. To complete all the work among all the exploration sites in time, it may be necessary to allow several drilling rigs to perform work at the same site.Yet, in the real world, unforeseen circumstances can affect drilling time, and that, if disregarded, can lead to a disruption of the work plan. Thus, in this problem, we maximize possible deviations of drilling times from expected values when there is still a feasible solution to perform all well-drilling requests in time. At the same time, total traveling costs must be no more than a given threshold. It is a so-called threshold robustness approach.The described Drilling Rig Routing Problem (DRRP) differs from other well-studied variants of Vehicle Routing Problem (VRP) in that the work splitting affects the service time. There is a limited number of papers dealing with such problems and no papers about the robust formulation for them.This research proposes a mathematical model for the novel formulation of the DRRP with uncertainties and an Adaptive Large Neighborhood Search (ALNS) algorithm to solve it. The destruction operators work either at the route, customer, or visit level. The reconstruction operators take into account a possibility to change the work partition. Computational results for the algorithm and Gurobi solver show the dominance of the ALNS scheme for medium-and large-sized instances.

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