Two-sided online bipartite matching in spatial data: experiments and analysis

Research on Task Allocation Model of Takeaway Platform Based on RWS-ACO Optimization Algorithm

“…Experiments to verify that the algorithm has advantages; Wang et al [5] proposed to transform the combinatorial optimization problem into a task allocation function with load capacity and cooperation constraints, solve by the algorithm and verify effectiveness by experiment; Pan et al [6] proposed to add an adaptive threshold algorithm based on the GH algorithm, and experiments to verify that it has lower cost and higher utility; Chen et al [7] proposed a dynamic grouping allocation method to solve the conflicts generated in a dynamic environment, behaved well; Fu et al [8] proposed a two-stage allocation model to try to distribute tasks fairly and minimize costs, experiments to verify F-Aware is superior than others; Liang et al [9] proposed TWD and design a two-stage competition and cooperation model: competition optimization and negotiation and cooperation, maximizes personal income and gets the best solution. Miao et al [10] proposed an adaptive ant colony algorithm to solve the problem of local optimal solution, through experimental verification, global optimization can be achieved; Xia et al [11] proposed an improved tabu search algorithm to solve a planning model that takes the number of vehicles and cost as dual goals; Liu et al [12] used the greeedy-ot algorithm with optimized threshold to solve the task assignment problem; Song et al [13] adopted an online greedy algorithm to solve the task assignment problem of spatial crowdsourcing, realize distribution with the lowest cost; Li et al [14] adopted a bilateral online matching method to match workers with tasks.…”

Subgroup Fairness in Two-Sided Markets

“…In the model of [44], one part of the bipartite graph ("workers") is fixed and known in advance, while nodes from the other part ("jobs") arrive online and must immediately be matched or discarded [45][46][47]. This model has many applications in online advertising platforms [48,49]; a wide range of novel applications arise [50] in the sharing economy, including applications within task assignment in spatial crowd-sourcing, real-estate agencies, and food delivery [51][52][53][54]. Especially, in the application of ride-sharing platforms, it could be a powerful tool for taxi order dispatch systems [55].…”

Spatial Two-Sided Online Bottleneck Matching With Deadlines

“…There are a lot of existing studies focusing on the online matching problem in SC [2]- [13]. Most of the existing studies consider the maximum-cardinality optimization objective [3], [4], [13], [14], or the max-/min-sum-cost optimization objective [5]- [9], [12], [15]- [19]. And only two related studies [10], [11] consider the minimum bottleneck cost optimization objective as we consider in this paper.…”

“…Batch is proposed in [38] and is demonstrated as the stateof-art algorithm for the two-sided online maximum matching with deadlines in SC [14]. We slightly adjust Batch a bit to fit the FOBMD problem by calculating the optimal bottleneck matching in each batch.…”