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Development of deterministic collision-avoidance algorithms for routing automated guided vehicles

Pai, Arun S.
Fonte: Rochester Instituto de Tecnologia Publicador: Rochester Instituto de Tecnologia
Tipo: Tese de Doutorado
Relevância na Pesquisa
A manufacturing job spends a small portion of its total flow time being processed on machines, and during the remaining time, either it is in a queue or being transported from one work center to another. In a fully automated material-handling environment, automated guided vehicles (AGV) perform the function of transporting the jobs between workstations, and high operational costs are involved in these material-handling activities. Consequently, the AGV route schedule dictates subsequent work-center scheduling. For an AGV job transportation schedule to be effective, the issue of collisions amongst AGV during travel needs to be addressed. Such collisions cause stalemate situations that potentially disrupt the flow of materials in the job shop, adding to the non-value time of job processing, and thus, increase the material handling and inventory holding costs. The current research goal was to develop a methodology that could effectively and efficiently derive optimal AGV routes for a given set of transportation requests, considering the issue of collisions amongst AGV during travel. As part of the solution approach in the proposed work, an integer linear program was formulated in Phase I with the capability of optimally predicting the AGV routes for a deterministic set of transportation requests. Collision avoidance constraints were developed in this model. The model was programmed using OPL / Visual Basic...