Batching and Matching for Food Delivery in Dynamic Road Networks

Joshi, Manas; Singh, Arshdeep; Ranu, Sayan; Bagchi, Amitabha; Karia, Priyank; Kala, Puneet

doi:10.1109/icde51399.2021.00207

Cited by 13 publications

(17 citation statements)

References 11 publications

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“…Next, we formulate the problem of food delivery without any fairness consideration (Joshi et al 2021). In general, the objective is to allocate orders to delivery agents such that the waiting time for customers is minimized.…”

Section: Background: the Food Delivery Problemmentioning

confidence: 99%

“…(1) In the real world, we work with a data stream of orders and vehicles instead of sets. The typical strategy to circumvent this issue is to accumulate orders over a time window ∆ and assign this order set to available vehicles (Joshi et al 2021;Reyes et al 2018). This process is then repeated over the data stream.…”

Section: Background: the Food Delivery Problemmentioning

confidence: 99%

“…We now elaborate on the key steps. Definition 6 (Shortest Delivery Time (Joshi et al 2021)). The shortest delivery time for an order o is SDT…”

Section: Our Proposal: Fairfoodymentioning

confidence: 99%

“…In this section, we benchmark FAIRFOODY and establish: • Fairness: FAIRFOODY imparts more than 10X improvement in fairness over baselines. • Cost of fairness: FAIRFOODY maintains a comparable delivery time as that of FOODMATCH (Joshi et al 2021). Code is available at https://github.com/idea-iitd/fairfoody.…”

Section: Experimental Evaluationmentioning

confidence: 99%

“…Food order assignment: On the problem of food-delivery, FOODMATCH (Joshi et al 2021) is the only work to provide a realistic and scalable solution in food delivery domain.…”

Section: Related Workmentioning

confidence: 99%

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FairFoody: Bringing In Fairness in Food Delivery

Gupta

Yadav

Nair

et al. 2022

AAAI

Self Cite

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Along with the rapid growth and rise to prominence of food delivery platforms, concerns have also risen about the terms of employment of the ``gig workers'' underpinning this growth. Our analysis on data derived from a real-world food delivery platform across three large cities from India show that there is significant inequality in the money delivery agents earn. In this paper, we formulate the problem of fair income distribution among agents while also ensuring timely food delivery. We establish that the problem is not only NP-hard but also inapproximable in polynomial time. We overcome this computational bottleneck through a novel matching algorithm called FairFoody. Extensive experiments over real-world food delivery datasets show FairFoody imparts up to 10 times improvement in equitable income distribution when compared to baseline strategies, while also ensuring minimal impact on customer experience.

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Section: Background: the Food Delivery Problemmentioning

confidence: 99%

Section: Background: the Food Delivery Problemmentioning

confidence: 99%

“…We now elaborate on the key steps. Definition 6 (Shortest Delivery Time (Joshi et al 2021)). The shortest delivery time for an order o is SDT…”

Section: Our Proposal: Fairfoodymentioning

confidence: 99%

Section: Experimental Evaluationmentioning

confidence: 99%

“…Food order assignment: On the problem of food-delivery, FOODMATCH (Joshi et al 2021) is the only work to provide a realistic and scalable solution in food delivery domain.…”

Section: Related Workmentioning

confidence: 99%

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FairFoody: Bringing In Fairness in Food Delivery

Gupta

Yadav

Nair

et al. 2022

AAAI

Self Cite

View full text Add to dashboard Cite

show abstract

Algorithms for Online Car-Sharing Problem

Guo

Luo

2022

Algorithms and Discrete Applied Mathematics

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Profit and Satisfaction Aware Order Assignment for Online Food Delivery Systems Exploiting Water Wave Optimization

et al. 2022

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Online Food delivery, a specialized application of mobile crowdsourcing, has accelerated its popularity due to rushed urban lifestyle in recent times. The food delivery order assignment to workers that maximizes the service qualities, such as maximization of workers' profit and minimization of order completion time to enhance the customer satisfaction at the same time, is a challenging problem. Existing works in the literature are limited either by focusing solely on minimizing order completion time or reduction of cost incurred in delivery of orders. In this paper, we develop a framework for optimal assignment of food delivery orders to workers as a multi-objective linear programming (MOLP) problem that makes a trade-off in between the worker profit and customer satisfaction. Due to NP-hardness of the above MOLP, a polynomial time solution of the food delivery problem has been developed, namely WWOFooD, exploiting Water Wave Optimization, a meta-heuristic algorithm. The WWOFooD not only explores ways of enhancing service quality of the customers, but also ensures giving additional incentives to the workers providing faster and reliable food delivery services. The results of simulation experiments depict that the WWOFooD offers competitive workers' profit as well as significantly enhances customer satisfaction compared to the state-of-the-art works.

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Batching and Matching for Food Delivery in Dynamic Road Networks

Cited by 13 publications

References 11 publications

FairFoody: Bringing In Fairness in Food Delivery

FairFoody: Bringing In Fairness in Food Delivery

Algorithms for Online Car-Sharing Problem

Profit and Satisfaction Aware Order Assignment for Online Food Delivery Systems Exploiting Water Wave Optimization

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