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- W2900507002 abstract "Automation of on-site scheduling and route planning of units in a mining operationpresents interesting challenges. The dynamic properties of real-life operations necessitateAI-inspired decentralized methods, which tend to be more robust under realconditions. Moreover, route planning in a mining environment, consisting of narrowpassageways, requires vehicles to communicate and cooperate for safe and efficienttransportation.We model this as a dynamic multiple-agent pickup and delivery problem; aproblem in which multiple agents cooperate to complete transportation tasks thatare revealed continuously. Taking inspiration from novel solutions, using auction-likebidding systems based on genetically optimized heuristics, we tackle the pickup anddelivery problem (PDP) from two different angles. Firstly, we show that existingsolutions to the planar variant of the PDP can be improved by giving agents theability to communicate. Secondly, we present a solution method to the PDP ina shared space environment, applicable for real world scenarios such as a miningoperation. Apart from using the aforementioned bidding system to assign tasks toagents, we also implement a method for solving decentralized multiple-agent pathfinding." @default.
- W2900507002 created "2018-11-29" @default.
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- W2900507002 date "2018-01-01" @default.
- W2900507002 modified "2023-09-24" @default.
- W2900507002 title "Self-organizing multi-agent systems for shared space operations: Using genetic algorithms and contract net protocols to solve the pickup and delivery problem" @default.
- W2900507002 hasPublicationYear "2018" @default.
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