Assignment rules in robotic mobile fulfilment systems for online retailers

Zou, Bipan; Gong, Yeming; Xu, Xianhao; Yuan, Zhe

doi:10.1080/00207543.2017.1331050

Cited by 107 publications

(48 citation statements)

References 23 publications

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“…Kiva system is pointed out to have poor cube utilization but higher flexibility and scalability over mini-load system in [14]. Therefore, RMFS is thought to be suitable for contemporary E-commerce warehouses which have fluctuated customer demands and large assortments of products [15].…”

Section: Literature Reviewmentioning

confidence: 99%

A Comprehensive Framework for the Design of Modular Robotic Mobile Fulfillment Systems

Wang

Zheng

et al. 2020

IEEE Access

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This paper focuses on the design of modular Robotic Mobile Fulfillment Systems. A Robotic Mobile Fulfillment System is an automated storage and retrieval system, in which mobile robots are deployed to deliver storage shelves for picking operation. This paper proposes a modular robotic system with aisle-captive robots for small and medium-sized logistics warehouses. Then analytical models, including a bottleneck-based model and an open queueing network model, are developed to estimate system throughput and average order flow time. Last, a two-stage design framework is proposed to rapidly identify an optimal system configuration. The main contributions are that: first, the proposed modular robotic system is free of traffic congestion and blocking; second, the comprehensive framework highlights some significant guidelines for warehouse developers during the ''conceptualization'' phase of system development. Simulation experiments indicate that the open queueing network model can provide accurate system performance estimation. The effectiveness of the proposed design framework is validated through practical application in real cases. INDEX TERMS Robotic mobile fulfillment system, material handling, open queueing network, logistics warehouses.

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Section: Literature Reviewmentioning

confidence: 99%

A Comprehensive Framework for the Design of Modular Robotic Mobile Fulfillment Systems

Wang

Zheng

et al. 2020

IEEE Access

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“…They find that it is better to replenish pods before they are entirely empty, even with multiple pods per SKU. [19] use semi-open queueing networks to analyze the policy for assigning robots to pick stations. The authors find that the random policy is significantly outperformed by the proposed handling-speeds-based assignment rule when facing varying service rates of the pickers.…”

Section: Related Workmentioning

confidence: 99%

Decision rules for robotic mobile fulfillment systems

Merschformann

Tessensohn

Koster

et al. 2019

Operations Research Perspectives

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The Robotic Mobile Fulfillment Systems (RMFS) is a new type of robotized, parts-to-picker material handling system, designed especially for e-commerce warehouses. Robots bring movable shelves, called pods, to workstations where inventory is put on or removed from the pods. This paper simulates both the pick and replenishment process and studies the order assignment, pod selection and pod storage assignment problems by evaluating multiple decision rules per problem. The discrete event simulation uses realistic robot movements and keeps track of every unit of inventory on every pod. We analyze seven performance measures, e.g. throughput capacity and order due time, and find that the unit throughput is strongly correlated with the other performance measures. We vary the number of robots, the number of pick stations, the number of SKUs (stock keeping units), the order size and whether returns need processing or not. The decision rules for pick order assignment have a strong impact on the unit throughput rate. This is not the case for replenishment order assignment, pod selection and pod storage. Furthermore, for warehouses with a large number of SKUs, more robots are needed for a high unit throughput rate, even if the number of pods and the dimensions of the storage area remain the same. Lastly, processing return orders only affects the unit throughput rate for warehouse with a large number of SKUs and large pick orders.

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“…A robotic mobile fulfilment system (RMFS) is a robot-based automated storage and parts-to-picker order picking system which is suited for distribution centres that face strong demand fluctuations and large assortments of small products [1]. Pioneered by famous Kiva systems, the RMFS is increasingly used in the ecommerce fulfilment centres to increase throughput capacity, reduce operational cost, and improve flexibility [2].…”

Section: Introductionmentioning

confidence: 99%

“…A decomposition procedure using a simulated annealing scheme and beam search mechanism was provided to solve the resulting decision problem. Zou et al [2] proposed a handling-speeds-based assignment rule and designed a neighbourhood search approach to find a near optimal assignment rule of workstations to robots to improve the system performance. They also build a semiopen queuing network to estimate the performance of the RMFS and used a two-phase approximation method to solve the SOQN.…”

Section: Introductionmentioning

confidence: 99%

A Building‐Block‐Based Genetic Algorithm for Solving the Robots Allocation Problem in a Robotic Mobile Fulfilment System

Zhang

Weng

2019

Mathematical Problems in Engineering

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Robotic mobile fulfilment system (RMFS) is an efficient and flexible order picking system where robots ship the movable shelves with items to the picking stations. This innovative parts-to-picker system, known as Kiva system, is especially suited for e-commerce fulfilment centres and has been widely used in practice. However, there are lots of resource allocation problems in RMFS. The robots allocation problem of deciding which robot will be allocated to a delivery task has a significant impact on the productivity of the whole system. We model this problem as a resource-constrained project scheduling problem with transfer times (RCPSPTT) based on the accurate analysis of driving and delivering behaviour of robots. A dedicated serial schedule generation scheme and a genetic algorithm using building-blocks-based crossover (BBX) operator are proposed to solve this problem. The designed algorithm can be combined into a dynamic scheduling structure or used as the basis of calculation for other allocation problems. Experiment instances are generated based on the characteristics of RMFS, and the computation results show that the proposed algorithm outperforms the traditional rule-based scheduling method. The BBX operator is rapid and efficient which performs better than several classic and competitive crossover operators.

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Assignment rules in robotic mobile fulfilment systems for online retailers

Cited by 107 publications

References 23 publications

A Comprehensive Framework for the Design of Modular Robotic Mobile Fulfillment Systems

A Comprehensive Framework for the Design of Modular Robotic Mobile Fulfillment Systems

Decision rules for robotic mobile fulfillment systems

A Building‐Block‐Based Genetic Algorithm for Solving the Robots Allocation Problem in a Robotic Mobile Fulfilment System

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