A capacitated biobjective location problem with uniformly distributed demands in the UAV‐supported delivery operation

Abstract

In recent years, small unmanned aerial vehicles have been used to deliver medicine and goods as a solution to severe traffic jams and to serve the purpose of fast and effective delivery, especially for medical and emergency applications where time is vital. On the other hand, in the competitive market of today, retailers are considering the use of drones to minimize the customers' waiting times and as a way to lower their transportation costs. This study aims to develop a biobjective mathematical model to account for the optimum number and spatial location of facilities among a set of candidate locations such that the total travel distance, costs, and lost demand are minimized simultaneously. It is assumed that the demand occurrence follows a Poisson distribution and is uniformly distributed along the network edges. The proposed biobjective capacitated facility location model is NP-hard, thus nondominated sorting genetic algorithm II and reference-point based nondominated sorting genetic algorithm are applied to solve the problem. The performance of the algorithms, quality of solutions, and the results are investigated and discussed.

Managing the drone revolution: A systematic literature review into the current use of airborne drones and future strategic directions for their effective control

“…Initial analysis indicates combined truck and drone delivery systems are a more efficient method of logistics delivery systems than current approaches ( Ferrandez et al, 2016 ; Chung, 2018 ; Carlsson and Song, 2017 ; Liu et al, 2018 ), Wang et al (2019) . However serial delivery systems may be more efficient still ( Sharvarani et al, 2019b ) and overall delivery considerations need further analysis, such as preparation time for deliveries which are different between truck vs. drone delivery ( Swanson, 2019 ). Further research in different urban contexts may yield different results (e.g.…”

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“…The latter is, for instance, pursued by Torabbeigi et al (2020), who apply a straightforward variant of the set covering problem to this problem. A similar cost-oriented setting, considering depot erection and drone procurement costs, is considered by Shavarani et al (2020). Considering a competitive environment, where different online retailers compete with each other, Baloch and Gzara (2020) provide a nonlinear mathematical model as well as logic-based benders decomposition approach to decide on which facilities should be opened, so that the overall profitability of the retailer is maximized.…”

“…Staffing and fleet sizing Shavarani et al (2020), Shavarani et al (2019), and Chauhan et al (2019) do not only investigate the strategic depot location problem, but simultaneously integrate the tactical drone fleet sizing problem. Liu et al (2019) propose a two-stage stochastic program to handle uncertain parcel demands.…”

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“…Besides, Shavarani et al. (2020) developed a biobjective mathematical model to account for the optimum number and spatial location of facilities among a set of candidate locations such that the total travel distance, costs, and lost demand are minimized simultaneously. Another possible relationship between objectives could be the reduction of energy consumption while minimizing the time or distance and vice versa .…”