HGHA: task allocation and path planning for warehouse agents

Liu, Yandong; Han, Dong; Wang, Lujia; Xu, Cheng‐Zhong

doi:10.1108/aa-10-2020-0152

Cited by 14 publications

(5 citation statements)

References 15 publications

(13 reference statements)

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“…As a result, heuristic path planning approaches are commonly used in multi-robot scenarios. A hierarchical algorithm combining optimization and multi-agent path-finding (MAPF) is proposed [27] . The top-level is the genetic algorithm (GA), allocating tasks to agents in an optimized way.…”

Section: Related Workmentioning

confidence: 99%

Multi-agent Task Allocation based on NSGA-II in a Warehouse Environment

Peng,

An,

et al. 2024

Preprint

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Multi-agent systems (MAS) can be widely applied in warehouse management to enhance logistics operation efficiency, reduce costs, and improve decision-making. In a MAS, robots can serve as agents to optimize the routing and scheduling of shipments, reducing delivery times and improving customer satisfaction in the warehouse environment. It is widely recognized that the more robots are deployed, the higher efficiency logistics operation will be. However, with the increasing number of robots, a growing number of challenges emerge, particularly in the domain of task allocation—a process aimed at assigning tasks to a group of robots to achieve a common goal. The task allocation often requires multi-objective optimization to balance various factors. This paper presents an efficient multi-agent task allocation algorithm that can handle both static and dynamic task allocation. To handle static tasks, the paper employs the NSGA2 algorithm, which can handle multi-objective optimization, to efficiently generate scheduling schemes and assign agents in the warehouse to execute tasks. For dynamic tasks, an auction-bid scheme is employed to quickly respond to task changes and ensure the efficient completion of the task. Meanwhile, we also design an effective scheme traffic-rules based to sufficiently avoid the robot collision. The simulation results demonstrated the capability of our algorithm to efficiently allocate tasks and plan the shortest path based on A*. Moreover, the algorithm effectively minimizes both the sum of the travel costs over all robots and the maximum individual travel cost over all robots simultaneously.

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Section: Related Workmentioning

confidence: 99%

Multi-agent Task Allocation based on NSGA-II in a Warehouse Environment

Peng,

An,

et al. 2024

Preprint

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“…Logistics activities comprehend transportation, warehousing, inventory management, order processing, information systems and packaging. The choice of the LSPs partner is a diffused issue in the literature [156][157][158][159][160]. The use of 3PLs is influenced by the duration of the relationships, the geographical dispersion of customers and vendors, the type of goods traded and the type of contracts [161].…”

Section: Outbound Logisticsmentioning

confidence: 99%

Implementing E-Commerce from Logistic Perspective: Literature Review and Methodological Framework

et al. 2022

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E-commerce is always more diffused as a selling channel around the whole world market, and its importance has increased and continues to increase with the COVID-19 pandemic emergency. It provides enterprises a lot of opportunities, as the importance of physical stores to sell goods is bypassed. However, it has also changed the role of logistics in the supply chain. For this reason, this work aims to identify the main logistics research areas related to e-commerce implementation and the factors and key performance indicators, which should be taken into account for each logistics research area, with particular attention to sustainable aspects. For doing this, a structured and comprehensive literature analysis is carried out. Keywords associated with e-commerce and logistics areas are matched to identify the most interesting works related to its implementation. From the analysis, five main research areas are identified: Supply Chain Network Design (SCND); Outbound Logistics (OL); Reverse Logistics (RL); Warehousing (WR); and IT and data management (E-IT). For each area, key factors, strategies and performance indicators have been identified. Finally, a methodological framework that summarizes the results of the analysis is presented; this is a useful tool for managers to implement or expand their e-commerce business. Many works are focused on one research area, carrying out critical factors, models, and methods to implement that topic. Instead, the methodological framework presented here summarizes multiple research areas from a logistic point of view, identifying for each one input and output variables and how they influence each other.

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“…Furthermore, due to their global search characteristics, the FHMOGA may not be able to adapt to dynamically changing environments and task requirements during actual task executions. This algorithm may also require complex communication and coordination mechanisms and may be affected by the diversity and quality of the solutions [26].…”

Section: Introductionmentioning

confidence: 99%

An Improved Reeds–Shepp and Distributed Auction Algorithm for Task Allocation in Multi-AUV System with Both Specific Positional and Directional Requirements

Li,

Zhu,

Chen

et al. 2024

JMSE

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Task assignment is of paramount importance in multi-AUV systems, particularly in applications such as bridge inspection where task execution is direction-specific. In such scenarios, the underactuation of AUVs is a critical factor that cannot be ignored. Therefore, it is essential to consider the AUV’s kinematic model comprehensively to ensure minimal energy consumption during task execution. In this paper, we introduce an improved Reeds–Shepp algorithm in conjunction with a distributed auction approach. We treat AUVs as car-like models in our approach, paying meticulous attention to their operational characteristics during path planning. Importantly, we effectively utilize their backward driving capabilities. Our analysis reveals that this model successfully fulfills the directional requirements of detection tasks. Furthermore, the distributed auction approach optimizes the overall task distribution in the multi-AUV system. We support our method with simulation results that underscore its effectiveness.

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HGHA: task allocation and path planning for warehouse agents

Cited by 14 publications

References 15 publications

Multi-agent Task Allocation based on NSGA-II in a Warehouse Environment

Multi-agent Task Allocation based on NSGA-II in a Warehouse Environment

Implementing E-Commerce from Logistic Perspective: Literature Review and Methodological Framework

An Improved Reeds–Shepp and Distributed Auction Algorithm for Task Allocation in Multi-AUV System with Both Specific Positional and Directional Requirements

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