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This research focuses on the development of an artificial multiple intelligence system (AMIS) for solving multi-visit scheduling and routing of multi-heterogeneous resources. The proposed method has been developed as a decision-making tool for solving mechanical sugarcane harvest operations which have been replacing the manual harvesting system with the sugarcane field burning. The mechanical sugarcane harvesting system is a fresh one with a high potential reduction of CO2 emission. Two resources which are fuel service staff teams and technician teams were considered to support the mechanical harvester operations in order to improve the harvesters’ productivity and stability of its sugarcane supply by minimizing the downtime or waiting time of harvesters. Based on this approach, not only the sugar production is efficient, but also the harvesting which is the inbound activity is fuel-efficient. This problem …