Methodology for the efficient distribution a manufacturing ontology to a multiagent system utilizing a relevant Meta-Ontology

Author(s):  
M. Georgoudakis ◽  
C. Alexakos ◽  
A.P. Kalogeras ◽  
J. Gialelis ◽  
S. Koubias
2018 ◽  
Vol 6 (5) ◽  
pp. 144-149
Author(s):  
H. Kousar ◽  
◽  
◽  
B.R.P. Babu

2021 ◽  
Vol 13 (4) ◽  
pp. 168781402110106
Author(s):  
John Rios ◽  
Rodrigo Linfati ◽  
Daniel Morillo-Torres ◽  
Iván Derpich ◽  
Gustavo Gatica

An efficient distribution center (DC) is one that receives, stores, picks and packs products into new logistics units and then dispatches them to points of sale at the minimal operating cost. The picking and packing processes represent the highest operating cost of a DC, and both require a suitable space for their operation. An effective coordination between these zones prevents bottlenecks and has a direct impact on the DC’s operational results. In the existing literature, there are no studies that optimize the distribution of the picking and packing areas simultaneously while also reducing operating costs. This article proposes an integer nonlinear integer programming model that minimizes order preparation costs. It does so by predicting customer demand based on historical data and defining the ideal area for picking and packing activities. The model is validated through a real case study of seven clients and fifteen products. It achieves a [Formula: see text] reduction in operating costs when the optimal allocation of the picking and packing areas is made.


2021 ◽  
Vol 7 ◽  
pp. 2294-2301
Author(s):  
Diyako Ghaderyan ◽  
Fernando Lobo Pereira ◽  
A. Pedro Aguiar

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Liu He ◽  
Haoning Xi ◽  
Tangyi Guo ◽  
Kun Tang

Path planning for the multiagent, which is generally based on the artificial potential energy field, reflects the decision-making process of pedestrian walking and has great importance on the field multiagent system. In this paper, after setting the spatial-temporal simulation environment with large cells and small time segments based on the disaggregation decision theory of the multiagent, we establish a generalized dynamic potential energy model (DPEM) for the multiagent through four steps: (1) construct the space energy field with the improved Dijkstra algorithm, and obtain the fitting functions to reflect the relationship between speed decline rate and space occupancy of the agent through empirical cross experiments. (2) Construct the delay potential energy field based on the judgement and psychological changes of the multiagent in the situations where the other pedestrians have occupied the bottleneck cell. (3) Construct the waiting potential energy field based on the characteristics of the multiagent, such as dissipation and enhancement. (4) Obtain the generalized dynamic potential energy field by superposing the space potential energy field, delay potential energy field, and waiting potential energy field all together. Moreover, a case study is conducted to verify the feasibility and effectiveness of the dynamic potential energy model. The results also indicate that each agent’s path planning decision such as forward, waiting, and detour in the multiagent system is related to their individual characters and environmental factors. Overall, this study could help improve the efficiency of pedestrian traffic, optimize the walking space, and improve the performance of pedestrians in the multiagent system.


2009 ◽  
Vol 24 (3) ◽  
pp. 16-25 ◽  
Author(s):  
Martin Rehák ◽  
Michal Pechoucek ◽  
Martin Grill ◽  
Jan Stiborek ◽  
Karel Bartoš ◽  
...  

1996 ◽  
Vol 24 (6) ◽  
pp. 599-620 ◽  
Author(s):  
Thomas J. Sheffler ◽  
Robert Schreiber ◽  
William Pugh ◽  
John R. Gilbert ◽  
Siddhartha Chatterjee

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