A Novel Hybrid Algorithm for Order Picking Optimization in Automated Warehouse

Hu, Huaining; Lu, Li; Zhi-jun, LV

doi:10.23919/chicc.2018.8484006

Cited by 3 publications

(1 citation statement)

References 4 publications

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“…They further formulate the retrieval jobs of stackers as combinatorial optimization problems, such as the Travelling Salesman Problem (TSP) [20]- [27], so that many optimization algorithms can be applied to solve the stacker scheduling problem. These algorithms include HGA-VNS Algorithm [21], Combination of Free Search and Amendment Circle Algorithm [22], Genetic Algorithm [23], Non-dominant Sequencing Genetic Algorithm with Elite Strategy [24] and Genetic Particle Swarm Algorithm [25]. Li et al studied the utilization of stackers in the tobacco industry and solved the coordination problem of the Automated Storage System and Retrieval System [26]; through the engineering test cases, the effectiveness of their designed algorithm has been demonstrated.…”

Section: Related Workmentioning

confidence: 99%

Dynamic Order-Based Scheduling Algorithms for Automated Retrieval System in Smart Warehouses

et al. 2021

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Section: Related Workmentioning

confidence: 99%

Dynamic Order-Based Scheduling Algorithms for Automated Retrieval System in Smart Warehouses

et al. 2021

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Efficient Order-based Scheduling Algorithms for Automated Retrieval System (ARS) in Smart Warehouses

Liu

Liew

Ooi

et al. 2020

2020 20th International Conference on Control, Automation and Systems (ICCAS)

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Multiple-Rack Strategies Using Optimization of Location Assignment Based on MRCGA in Miniload Automated Storage and Retrieval System

Guan

Wang

et al. 2023

Processes

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This paper aimed to introduce multiple-rack strategies in miniload automated storage and retrieval systems (AS/RSs), which included first fit (FF) and best fit (BF) assignment methods based on a matrix real-coded genetic algorithm (MRCGA) in the storage and retrieval process. We validated the probability occurrence of item sizes as a contributory factor in multiple-rack strategies, and compared their capacities, utilization of units and space by equal probabilities or the 80/20 law. According to the analytical methods, BF showed a reduction of more than 11.2% than FF on travel distance, and Type B-FF, Type B-BF and Type C-BF were better able to meet high-density requirements. These strategies provide diversified storage and retrieval solutions for the manufacturing and express delivery industry.

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A Novel Hybrid Algorithm for Order Picking Optimization in Automated Warehouse

Cited by 3 publications

References 4 publications

Dynamic Order-Based Scheduling Algorithms for Automated Retrieval System in Smart Warehouses

Dynamic Order-Based Scheduling Algorithms for Automated Retrieval System in Smart Warehouses

Efficient Order-based Scheduling Algorithms for Automated Retrieval System (ARS) in Smart Warehouses

Multiple-Rack Strategies Using Optimization of Location Assignment Based on MRCGA in Miniload Automated Storage and Retrieval System

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