Integrated cross-supplier order and logistic scheduling in cloud manufacturing

Wu, Qiao; Xie, Naiming; Zheng, Shaoxiang

doi:10.1080/00207543.2020.1867921

Cited by 19 publications

(10 citation statements)

References 34 publications

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“…According to Choudhury et al (2021), implementation of robots in warehouses dramatically increases the efficiency of the supply chain, and modern 3D technology can be used for warehouse space design and facility planning to increase capacity and productivity. Wu et al (2021) demonstrate that cloud manufacturing platforms can improve the efficiency of supplier ordering and logistics scheduling processes. Bag et al (2020a) also reveal that Logistics 4.0 ensures timely delivery and supply and enhances firms' flexibility and responsiveness.…”

Section: Potential Impacts Of Logistics 40 On Corporate Sustainabilitymentioning

confidence: 98%

“…The literature affirms that Industry 4.0 initiatives yield economic benefits, mainly due to the reduction of costs (particularly operating and labour costs), the increase of productivity and efficiency and the enhancement of customer satisfaction by reducing lead time and improving shipping and information accuracy, responsiveness and product customisation (Hofmann and R€ usch, 2017;Barreto et al, 2017;Edirisuriya et al, 2018;Strandhagen et al, 2017;Majeed and Impact of Logistics 4.0 Rupasinghe, 2017;Nikoli ci c et al, 2015;Ghadge et al, 2020;Ejsmont et al, 2020;Ghobakhloo, 2020;Bai et al, 2020;Wu et al, 2021;Queiroz et al, 2019;Bag et al, 2020a;Salam, 2019;Choudhury et al, 2021;Dubey et al, 2019a). Majeed and Rupasinghe (2017), for example, discuss the implementation of RFID technology by Walmart and Procter and Gamble, showing that revenue can increase considerably with the reduction of inventory, the improvement of service and the reduction of administrative expenses that result from the redesign of a business process.…”

Section: Potential Impacts Of Logistics 40 On Corporate Sustainabilitymentioning

confidence: 98%

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The impact of Logistics 4.0 on corporate sustainability: a performance assessment of automated warehouse operations

Nantee

Sureeyatanapas

2021

BIJ

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PurposeThe purpose of this study is to gain a better understanding of the impacts of Logistics 4.0 initiatives (focusing on automated warehousing systems) on the economic, environmental and social dimensions of firms' sustainability performance. To achieve this objective, a new framework for the assessment of sustainable warehousing in the 4.0 era is developed.Design/methodology/approachThe framework, developed via the item-objective congruence index, Q-sort method and interviews with experts, is employed to assess performance changes through management interviews in two warehousing companies after the implementation of automation technologies.FindingsMost aspects of both companies' sustainability performance are considerably improved (e.g. productivity, accuracy, air emission, worker safety and supply chain visibility); however, the outcome for some criteria might be worsened or improved depending on each company's solutions and strategies (e.g. increasing electricity bills, maintenance costs and job losses).Practical implicationsThe findings provide insight into the effective implementation of warehousing technologies. The proposed framework is also a valid and reliable instrument for sustainability assessment for warehousing operators, which companies can utilise for self-assessment.Originality/valueThis paper contributes to establishing a body of literature that explores the previously unclarified effects of Logistics 4.0 on firms' sustainability performance. The proposed framework, which captures critical concerns of corporate sustainability and technological adaptation, is also the first of its kind for warehouse performance assessment.

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Section: Potential Impacts Of Logistics 40 On Corporate Sustainabilitymentioning

confidence: 98%

Section: Potential Impacts Of Logistics 40 On Corporate Sustainabilitymentioning

confidence: 98%

The impact of Logistics 4.0 on corporate sustainability: a performance assessment of automated warehouse operations

Nantee

Sureeyatanapas

2021

BIJ

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“…Hu et al [10] established a scheduling metric assessment based on five aspects, task loadability, task reliability, manufacturing efficiency, manufacturing resource richness, and IoT matching, and used the AHP method to determine the relative weights of each factor at each level to transform the multi-objective optimisation into a single-objective problem, improving timeliness of the cloud manufacturing platform. Li et al [11] studied the task scheduling of industrial robots under different enterprises under cloud manufacturing and proposed three sub-task scheduling strategies based on the three optimisation objectives of balanced Wu et al [21] √…”

Section: Literature Review 21 Cloud Manufacturing Scheduling Problemsmentioning

confidence: 99%

“…Shi et al [27] established an optimisation model with the objectives of cost minimisation and time minimisation and proposed a new algorithm combining a bat algorithm and a metacellular automaton for a cloud manufacturing resource scheduling new algorithm, which transforms the continuous scheduling problem into a discrete problem to obtain the optimal solution. Wu et al [21] studied the integrated cross-supplier order and logistics scheduling problem, and developed a strategy based on the improved mix-and-shuffle frog jumping algorithm to solve the model.…”

Section: Scheduling Optimisation Algorithm Problemmentioning

confidence: 99%

Resource Scheduling Optimisation Study Considering Both Supply and Demand Sides of Services under Cloud Manufacturing

Zhang,

Li,

Duan

et al. 2024

Systems

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In cloud manufacturing environments, the scheduling of multi-user manufacturing tasks often fails to consider the impact of service supply on resource allocation. This study addresses this gap by proposing a bi-objective multi-user multi-task scheduling model aimed at simultaneously minimising workload and maximising customer satisfaction. To accurately capture customer satisfaction, a novel comprehensive rating index is introduced, integrating the actual completion cost, time, and processing quality against customer expectations. Furthermore, vehicle constraints are incorporated into the model to accommodate potential delays in transport vehicle availability, thereby enhancing its alignment with real-world manufacturing settings. The proposed mathematical model is solved using an improved three-stage genetic algorithm, which integrates the k-means algorithm and a real-time sequence scheduling strategy to optimise solution quality. Validation against alternative algorithms across various case scales demonstrates the efficacy of the approach in providing practical scheduling solutions for real-case scenarios.

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“…Rahman et al proposed a novel scheduling approach capable of ensuring integrated operations for multiple automated transport vehicles [1]. Qiao Wu et al developed a strategy based on an improved shuffled frogleaping algorithm for solving an integrated cross-supplier order and logistic scheduling problem [2]. Despite their success, in recent years, researchers seek to improve the efficiency of emergency material scheduling.…”

Section: Introductionmentioning

confidence: 99%

An AI Planning Approach to Emergency Material Scheduling Using Numerical PDDL

Yang¹,

Liang²

2022

Atlantis Highlights in Intelligent Systems

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Emergency material planning and scheduling aims to schedule emergency material to destination efficiently to reduce property losses and personal casualties caused by material shortage. Existing researches usually rely on optimization of transportation routes. They ignore the rich scenarios in which human and material resources participate in scheduling simultaneously. Moreover, sudden emergencies may involve the supply of multiple material demand points. To address these issues, we propose an AI planning approach to model emergency material scheduling domain and construct a standard planning task using PDDL. Then a state-of-the-art planner is employed to solve the generated planning task. Experimental results show that the proposed approach can fit the actual situation of emergencies and give high-quality instruction to guide emergency material planning and scheduling.

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Integrated cross-supplier order and logistic scheduling in cloud manufacturing

Cited by 19 publications

References 34 publications

The impact of Logistics 4.0 on corporate sustainability: a performance assessment of automated warehouse operations

The impact of Logistics 4.0 on corporate sustainability: a performance assessment of automated warehouse operations

Resource Scheduling Optimisation Study Considering Both Supply and Demand Sides of Services under Cloud Manufacturing

An AI Planning Approach to Emergency Material Scheduling Using Numerical PDDL

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