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In the highly fragmented truckload transportation industry a substantial fraction of truck movements involves empty trucks, i.e., moves that reposition trucks. However, reducing the amount of truck repositioning is difficult because the need for a carrier to reposition its trucks depends on the interactions between the shippers the carrier is serving. Through collaboration, shippers may be able to identify and submit sequences of continuous loaded movements to carriers, reducing the carriers’ need for repositioning, and thus lowering the carriers’ costs. A portion of the carriers’ cost savings may be returned to the shippers in the form of lower prices. We discuss optimization technology that can be used to assist in the identification of repeatable, dedicated truckload continuous move tours with little truck repositioning. Timing considerations are critical to practical viability and a key focus of our efforts. We demonstrate the effectiveness of the algorithms developed on various randomly generated instances as well as on instances derived from data obtained from a strategic sourcing consortium for a $14 billion U.S. industry.

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