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This paper considers a joint pollution-routing and speed optimization problem(PRP-SO) where fuel costs and $\textit{CO}_2e$ emissions depend on the vehiclespeed, arc payloads, and road grades. We present two methods, one approximateand one exact, for solving the PRP-SO. The approximate strategy solveslarge-scale instances of the problem with a tabu search-based metaheuristiccoupled with an efficient fixed-sequence speed optimization algorithm. Thesecond strategy consists of a tailored branch-and-price (BP) algorithm in whichspeed optimization is managed within the pricing problem. We test both methodson modified Solomon benchmarks and newly constructed real-life instance sets.Our BP algorithm solves most instances with up to 50 customers and manyinstances with 75 and 100 customers. The heuristic is able to find near-optimalsolutions to all instances and requires less than one minute of computationaltime per instance. Results on real-world instances suggest several managerialinsights. First, fuel savings of up to 53\% are realized when explicitly takinginto account arc payloads and road grades. Second, fuel savings and emissionsreduction are also achieved by scheduling uphill customers later along theroutes. Lastly, we show that ignoring elevation information when planningroutes leads to highly inaccurate fuel consumption estimates.

The Pollution-Routing Problem with Speed Optimization and Uneven Topography