Abstract
In order to ensure an overall efficient production performance, the industrial experiences and research activities have demonstrated the interest of hybrid control systems, which couple a predictive scheduling with a distributed reactive control. In this context, it is commonly accepted that using the multi-agent systems (MAS) paradigm enhances the reactivity to treat disturbances and improves the decision making process of a shop floor. Each agent can have different capabilities (evolution, learning etc.) and the whole system, based on the agent interaction, leads emerging behaviours to dynamically adapt the production schedule. This paper is aimed to develop and simulate a negotiation scenario to deal with disturbed manufacturing processes. The scenario was implemented on the basis of TRACILOGIS test-bed platform. The negotiation protocol consists in setting the best sequential priority based on some performance indicators. This protocol is compared with a purely reactive production mode.
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Acknowledgements
The authors gratefully acknowledge the financial support of the CPER 2007–2013 Structuration du Pôle de Compétitivité Fibres Grand’Est (Competitiveness Fibre Cluster), through local (Conseil Général des Vosges), regional (Région Lorraine), national (DRRT and FNADT) and European (FEDER) funds used to implement the TRACILOGIS platform.
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Appendix: Simulation Run on the Basis of TRACILOGIS Test-Bed Platform
Appendix: Simulation Run on the Basis of TRACILOGIS Test-Bed Platform
Negotiation production mode | Reactive production mode | |||||||
---|---|---|---|---|---|---|---|---|
Run no. | Resource utilization rate in % | Lateness [M unit time] | Makespan [M unit time] | Resource utilization rate [%] | Lateness [M unit time] | Makespan [M unit time] | ||
M1 | M2 | M1 | M2 | |||||
1 | 57.638 | 9.041 | 18.034 | 4.213 | 52.8558 | 8.1424 | 25.378 | 4.936 |
2 | 58.292 | 8.919 | 20.563 | 4.153 | 52.7938 | 8.1256 | 25.413 | 4.932 |
3 | 54.409 | 7.872 | 25.137 | 4.453 | 53.2695 | 7.9293 | 26.183 | 4.972 |
4 | 56.482 | 8.8647 | 14.991 | 4.214 | 52.7212 | 8.0879 | 25.17 | 4.919 |
5 | 54.979 | 8.3198 | 18.767 | 4.453 | 52.1597 | 8.3806 | 23.965 | 4.858 |
6 | 57.179 | 8.6526 | 15.604 | 4.126 | 53.1261 | 8.1643 | 25.148 | 4.956 |
7 | 57.499 | 8.7195 | 15.984 | 4.765 | 52.0837 | 8.2883 | 24.216 | 4.857 |
8 | 55.149 | 8.3472 | 17.913 | 4.543 | 53.3881 | 8.1176 | 26.32 | 4.985 |
9 | 55.840 | 8.6255 | 21.859 | 4.654 | 53.0012 | 7.9846 | 25.174 | 4.948 |
10 | 54.207 | 8.028 | 22.995 | 4.358 | 53.0811 | 7.917 | 26.063 | 4.955 |
11 | 57.298 | 9.1398 | 19.411 | 4.398 | 52.9325 | 8.1433 | 25.068 | 4.944 |
12 | 57.456 | 8.9456 | 20.467 | 4.239 | 52.2755 | 8.5515 | 23.91 | 4.868 |
13 | 57.792 | 8.9819 | 15.446 | 4.543 | 52.195 | 7.9588 | 23.867 | 4.859 |
14 | 55.994 | 8.6523 | 21.682 | 4.675 | 52.7988 | 7.991 | 25.49 | 4.933 |
15 | 57.559 | 9.0872 | 20.071 | 4.267 | 52.9869 | 8.0779 | 25.383 | 4.953 |
16 | 55.845 | 8.9843 | 21.084 | 4.567 | 53.022 | 8.2144 | 25.165 | 4.947 |
17 | 57.466 | 9.1792 | 15.188 | 4.132 | 52.9281 | 7.8771 | 25.335 | 4.944 |
18 | 61.161 | 9.5158 | 16.537 | 4.657 | 52.3901 | 8.0342 | 24.304 | 4.879 |
19 | 60.747 | 9.0764 | 17.322 | 4.155 | 53.1266 | 7.8721 | 25.679 | 4.963 |
20 | 57.256 | 8.6505 | 15.533 | 4.458 | 52.6351 | 8.0341 | 24.901 | 4.912 |
21 | 56.655 | 9.0554 | 16.523 | 4.358 | 52.1935 | 8.4481 | 24.784 | 4.872 |
22 | 59.807 | 9.6894 | 17.085 | 4.307 | 53.3609 | 8.1554 | 26.494 | 4.987 |
23 | 56.425 | 8.557 | 19.225 | 4.752 | 54.1766 | 8.233 | 23.611 | 4.821 |
24 | 60.195 | 9.367 | 15.771 | 4.218 | 52.3789 | 8.5047 | 24.273 | 4.885 |
25 | 61.952 | 10.00 | 12.808 | 4.182 | 52.8363 | 8.107 | 25.109 | 4.931 |
26 | 60.385 | 9.142 | 12.654 | 4.219 | 53.4946 | 7.87 | 26.454 | 5.007 |
27 | 57.468 | 8.928 | 21.127 | 4.517 | 53.0372 | 7.8231 | 26.012 | 4.953 |
28 | 56.720 | 8.679 | 18.539 | 4.502 | 52.9587 | 8.0193 | 25.127 | 4.943 |
29 | 63.178 | 10.12 | 10.019 | 3.987 | 52.2012 | 8.3483 | 24.096 | 4.870 |
30 | 57.286 | 8.441 | 15.721 | 4.558 | 52.3998 | 8.08 | 24.379 | 4.889 |
31 | 56.055 | 8.149 | 18.875 | 4.762 | 53.0937 | 8.0205 | 25.896 | 4.959 |
32 | 60.848 | 9.435 | 15.101 | 4.204 | 53.6773 | 7.9681 | 26.478 | 5.022 |
33 | 56.047 | 9.095 | 21.409 | 4.571 | 52.9313 | 8.3785 | 25.48 | 4.944 |
34 | 58.812 | 9.111 | 16.331 | 4.368 | 52.9335 | 7.8164 | 25.638 | 4.941 |
35 | 55.530 | 8.400 | 21.212 | 4.559 | 53.3417 | 7.9585 | 26.564 | 4.984 |
36 | 56.186 | 8.387 | 23.44 | 4.69 | 52.991 | 7.9121 | 24.917 | 4.945 |
37 | 61.971 | 9.591 | 14.073 | 4.183 | 52.4133 | 8.1897 | 24.136 | 4.886 |
38 | 58.199 | 8.641 | 17.288 | 4.423 | 53.6607 | 7.8973 | 26.543 | 5.018 |
39 | 57.131 | 9.104 | 19.597 | 4.473 | 53.1413 | 7.6211 | 25.444 | 4.968 |
40 | 56.563 | 8.648 | 23.027 | 4.69 | 53.311 | 8.5276 | 25.603 | 4.979 |
41 | 58.364 | 8.944 | 18.927 | 4.398 | 53.0403 | 8.338 | 25.335 | 4.951 |
42 | 57.425 | 8.831 | 15.744 | 4.523 | 52.9237 | 8.0495 | 25.628 | 4.944 |
43 | 57.482 | 8.072 | 22.401 | 4.746 | 52.9941 | 7.888 | 25.488 | 4.943 |
44 | 64.297 | 9.900 | 11.281 | 4.073 | 53.1654 | 8.1327 | 25.78 | 4.965 |
45 | 54.768 | 8.299 | 22.378 | 4.74 | 53.1247 | 7.8174 | 25.989 | 4.964 |
46 | 57.778 | 8.828 | 20.311 | 4.482 | 52.6639 | 7.9374 | 25.199 | 4.914 |
47 | 62.478 | 9.6444 | 14.099 | 4.134 | 52.8076 | 8.0659 | 25.518 | 4.934 |
48 | 59.474 | 9.4307 | 18.039 | 4.47 | 52.8131 | 7.9705 | 25.3 | 4.928 |
49 | 55.102 | 8.466 | 18.669 | 4.717 | 52.0553 | 7.9994 | 24.664 | 4.853 |
50 | 60.780 | 9.306 | 14.527 | 4.331 | 52.2629 | 8.3151 | 24.559 | 4.873 |
Total | 2895.6 | 445.8 | 900.789 | 221.16 | 2644.1543 | 404.2846 | 1262.63 | 246.593 |
Average | 57.912 | 8.917 | 18.01578 | 4.4232 | 52.883086 | 8.085692 | 25.2526 | 4.93186 |
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Mezgebe, T.T., El Haouzi, H.B., Demesure, G., Pannequin, R., Thomas, A. (2018). A Negotiation Scenario Using an Agent-Based Modelling Approach to Deal with Dynamic Scheduling. In: Borangiu, T., Trentesaux, D., Thomas, A., Cardin, O. (eds) Service Orientation in Holonic and Multi-Agent Manufacturing. Studies in Computational Intelligence, vol 762. Springer, Cham. https://doi.org/10.1007/978-3-319-73751-5_29
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