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A Multi-objective Ant Colony Algorithm for the 1/3 Variant of the Time and Space Assembly Line Balancing Problem Manuel Chica, Óscar Cordón, Sergio Damas Joaquín Bautista
Summary ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Introduction ,[object Object],[object Object],[object Object]
SALBP and TSALBP  (1) ,[object Object],[object Object]
SALBP and TSALBP  (2) ,[object Object],[object Object]
SALBP and TSALBP  (3) ,[object Object],There are  4 TSALBP multi-objective variants . We have selected the  1/3 variant , which minimises the number of stations,  m , and their area,  A , given a fixed cycle time limit. We made this decision because it is the most realistic variant in the automotive industry.
The Multiple Ant Colony System (MACS)  (1) ,[object Object],[object Object],λ  weights the importance of the heuristic information of each ant, and  β  weights the heuristic information with respect to the pheromone trail
The Multiple Ant Colony System (MACS)  (2) ,[object Object],[object Object],[object Object],Average of the non-dominated solutions
Our MACS-based approach  (1) ,[object Object],[object Object],task a task c task e task d task b task f task g task h station 1 station 2 station 3 A  = 20  C  = 12 A  = 16  C  = 11 A  = 24  C  = 12
Our MACS-based approach  (2) ,[object Object],[object Object],The first one is related with the required  time of the task  and the number of successors: The second one related with the required  area   of the task  and the number of successors: Tasks having a large value of time and area and a high number of successors, are preferred to be allocated first.
Our MACS-based approach  (3) ,[object Object],[object Object]
Experiments  (1) ,[object Object],[object Object]
Experiments  (2) ,[object Object],[object Object],[object Object],[object Object]
Experiments  (3) ,[object Object],[object Object],[object Object],[object Object],[object Object]
Experiments  (4) ,[object Object],[object Object]
Experiments  (5) ,[object Object],[object Object]
Current work  (1) ,[object Object],[object Object],station 3 A m station 1 m A station 2 m A 0.2 0.5 0.9
Current work  (2) ,[object Object],[object Object],[object Object]
Current work  (3) ,[object Object],[object Object]
Concluding remarks ,[object Object],[object Object]
Future work  (1) ,[object Object],[object Object]
Future work  (2) ,[object Object],[object Object]
THANKS!

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Slides TSALBP ACO 2008

  • 1. A Multi-objective Ant Colony Algorithm for the 1/3 Variant of the Time and Space Assembly Line Balancing Problem Manuel Chica, Óscar Cordón, Sergio Damas Joaquín Bautista
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