Optimal Selection of Movable Shelves under Cargo-to-Person Picking Mode

Li, Z. P.; Zhang, J. L.; Zhang, H. J.

doi:10.2507/ijsimm16(1)co2

Cited by 32 publications

(17 citation statements)

References 25 publications

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“…In the future research, it is important to validate obtained results in an existing logistics facility and enriching the sensitivity analysis with changes of other parameters, as well as using software other than Plant Simulation, especially in order to compare the results. In forthcoming research, the author will reshape the simulation model in order to analyze the use of autonomous mobile robots and autonomous guided vehicles as, e.g., in [ 115 ]. It will also be profitable to transfer simulation methodology presented in this paper to other logistics facilities, e.g., freight terminals, since activity planning and optimization in these facilities can be realized by such simulation methods [ 116 , 117 ].…”

Section: Discussionmentioning

confidence: 99%

Sensitivity Analysis of Selected Parameters in the Order Picking Process Simulation Model, with Randomly Generated Orders

Kostrzewski

2020

Entropy

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Sensitivity analysis of selected parameters in simulation models of logistics facilities is one of the key aspects in functioning of self-conscious and efficient management. In order to develop simulation models adequate of real logistics facilities’ processes, it is important to input actual data connected to material flows on entry to models, whereas most models assume unified load units as default. To provide such data, pseudorandom number generators (PRNGs) are used. The original generator described in the paper was employed in order to generate picking lists for order picking process (OPP). This ensures building a hypothetical, yet close to reality process in terms of unpredictable customers’ orders. Models with applied PRNGs ensure more detailed and more understandable representation of OPPs in comparison to analytical models. Therefore, the author’s motivation was to present the original model as a tool for enterprises’ managers who might control OPP, devices and means of transport employed therein. The outcomes and implications of the contribution are connected to presentation of selected possibilities in OPP analyses, which might be developed and solved within the model. The presented model has some limitations. One of them is assumption that one mean of transport per one aisle is taken into consideration. Another limitation is the indirectly randomization of certain model’s parameters.

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Section: Discussionmentioning

confidence: 99%

Sensitivity Analysis of Selected Parameters in the Order Picking Process Simulation Model, with Randomly Generated Orders

Kostrzewski

2020

Entropy

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“…Contrasting to the random yield, the circulation loss of fresh produce items usually occurs after a farmer delivers products. Generally, the circulation loss of them can be managed by applying the preservation-technology activities [1,[6][7][8][9][10][11], improving warehouse and transportation processes [12,13] or using risk-sharing contracts [14][15][16][17][18][19][20][21][22][23]. The investment in such activities can reduce circulation loss rate and consequently can increase the available quantity of fresh produce items, and the coordination in such contracts can enhance the performance of the FSC system and its parties.…”

Section: Introductionmentioning

confidence: 99%

Modelling and Simulation of Fresh-Product Supply Chain Considering Random Circulation Losses

Fang¹,

Wang²,

Yuan³

et al. 2020

Int. j. simul. model.

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Random circulation losses of fresh products are also a great challenge that affects the decision-making of farmers and enterprises as well as the revenue management of both parties. Considering a freshproduct supply chain (FSC) comprising a single enterprise and a single farmer with random circulation losses, we explore the optimal ordering of the enterprise, optimal planting of the farmer, and risksharing mechanism of both participants. After modelling the optimal decision model of centralized FSC, we solve the optimal global solutions that exist uniquely. Then, a risk-sharing contract, called a wholesale price contract, is designed that can coordinate the decentralized FSC. Finally, a simulation of sensitivity analysis using MATLAB soft is figured out to explore the influence of random risks on the optimal solutions and the contract parameters. Furthermore, some conclusions and future researches are given.

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“…The remainder of this paper is organized as follows: Section 2 analyzes and models the main factors affecting the lubrication of wind turbines [11][12][13][14]; Section 3 introduces the principle of parallel control of multiple factors, formulates a preliminary lubrication scheme based on the predicted wind power, and adjusts the scheme in real time according to the error between the predicted data and actual data, as well as the sudden change of operating conditions; Section 4 proves the feasibility of the proposed control strategy through bearing wear experiments, and comparative simulations on wind turbine lubrication; Section 5 puts forward the conclusions.…”

Section: Introductionmentioning

confidence: 99%

Wind Turbine Lubrication Based on Parallel Control of Multiple Factors

Xiao-pin¹,

Liu²,

Kou³

et al. 2020

JESA

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The lubrication needs of wind turbines vary with the operating conditions. To provide a dynamic lubrication scheme for wind turbines under variable conditions, this paper designs a dynamically adjustable lubrication scheme through parallel control of multiple influencing factors. Based on mid- and long-term loads, the proposed scheme fully considers the influence of various sudden changes in addition to slowly changing factors like load, operating hours, and speed, such as to dynamically adjust the injection flow as per the specific operating condition of the turbine. The ideal lubrication effect was tracked through the adjustment of the injection flow or injection time, and used to determine the optimal dynamic lubrication control strategy during turbine operation. The proposed control strategy overcomes the defects of the traditional fixed-time fixed-flow lubrication approach, and provides reasonable on-demand lubrication schemes for wind turbines in different operating conditions. The on-demand injection of lubricant prevents under- or over-lubrication, reduces the rate of mechanical failure, and extends the service life of wind turbines. Suffice it to say that the proposed control strategy can lower power generation cost and save energy, making wind turbines more profitable.

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Optimal Selection of Movable Shelves under Cargo-to-Person Picking Mode

Cited by 32 publications

References 25 publications

Sensitivity Analysis of Selected Parameters in the Order Picking Process Simulation Model, with Randomly Generated Orders

Sensitivity Analysis of Selected Parameters in the Order Picking Process Simulation Model, with Randomly Generated Orders

Modelling and Simulation of Fresh-Product Supply Chain Considering Random Circulation Losses

Wind Turbine Lubrication Based on Parallel Control of Multiple Factors

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