China, like many developing countries, faces a difficult tradeoff between economic development an... more China, like many developing countries, faces a difficult tradeoff between economic development and environmental protection. Being the world’s largest producer and consumer of coal places a massive burden on China’s transportation and environmental systems. In 1989, energy shortages and runaway pollution prompted the World Bank and the Chinese State Planning Commission (SPC) to jointly undertake the China Coal Transport Study (CTS). At the time, China relied on coal for 73 percent of commercial energy, while coal accounted for 42 percent of rail freight. Rail transport, coal, and electricity were all suffering from debilitating shortages, which threatened China’s 10 percent annual economic growth. Meanwhile, SO2 and particulate levels were among the highest in the world, and CO2 emissions reached 11 percent of the world total — second after the United States.
ABSTRACT In recent years, transit planners are increasingly turning to simpler, faster, and more ... more ABSTRACT In recent years, transit planners are increasingly turning to simpler, faster, and more spatially detailed “sketch planning” or “direct demand” models for forecasting rail transit boardings. Planners use these models for preliminary review of corridors and analysis of station-area effects, instead of or prior to four-step regional travel demand models. This paper uses a sketch-planning model based on a multiple regression originally fitted to light-rail ridership data for 268 stations in nine U.S. cities, and applies it predictively to the Phoenix, Arizona light-rail starter line that opened in December, 2008. The independent variables in the regression model include station-specific trip generation and intermodal–access variables as well as system-wide variables measuring network structure, climate, and metropolitan-area factors. Here we compare the predictions we made before and after construction began to pre-construction Valley Metro Rail predictions and to the actual boardings data for the system’s first 6 months of operations. Depending on the assumed number of bus lines at each station, the predicted total weekday ridership ranged from 24,767 to 37,907 compared with the average of 33,698 for the first 6 months, while the correlation of predicted and observed station boardings ranged from r = 0.33 to 0.47. Sports venues, universities, end-of-line stations, and the number of bus lines serving each station appear to account for the major over- and under-predictions at the station level.
For location problems in which optimal locations can be at nodes or along arcs but no finite domi... more For location problems in which optimal locations can be at nodes or along arcs but no finite dominating set has been identified, researchers may desire a method for dispersing p additional discrete candidate sites along the m arcs of a network. This article develops and tests minimax and maximin models for solving this continuous network location problem, which we call the added‐node dispersion problem (ANDP). Adding nodes to an arc subdivides it into subarcs. The minimax model minimizes the maximum subarc length, while the maximin model maximizes the minimum subarc length. Like most worst‐case objectives, the minimax and maximin objectives are plagued by poorly behaved alternate optima. Therefore, a secondary MinSumMax objective is used to select the best‐dispersed alternate optima. We prove that equal spacing of added nodes along arcs is optimal to the MinSumMax objective. Using this fact we develop greedy heuristic algorithms that are simple, optimal, and efficient (O(mp)). Empirical results show how the maximum subarc, minimum subarc, and sum of longest subarcs change as the number of added nodes increases. Further empirical results show how using the ANDP to locate additional nodes can improve the solutions of another location problem. Using the p‐dispersion problem as a case study, we show how much adding ANDP sites to the network vertices improves the p‐dispersion objective function compared with (a) network vertices only and (b) vertices plus randomly added nodes. The ANDP can also be used by itself to disperse facilities such as stores, refueling stations, cell phone towers, or relay facilities along the arcs of a network, assuming that such facilities already exist at all nodes of the network.
Abstract: The diffusion of containerization has changed not only how general cargo is handled, bu... more Abstract: The diffusion of containerization has changed not only how general cargo is handled, but where. Using the Gini coefficient, we show that general cargo port traffic has become more concentrated from 1970 to 1988 because of four technological changes: ...
European Journal of Operational Research, Jul 1, 2010
This paper presents three heuristic algorithms that solve for the optimal locations for refueling... more This paper presents three heuristic algorithms that solve for the optimal locations for refueling stations for alternative-fuels, such as hydrogen, ethanol, biodiesel, natural gas, or electricity. The Flow-Refueling Location Model (FRLM) locates refueling stations to maximize the flow that can be refueled with a given number of facilities. The FRLM uses path-based demands, and because of the limitations imposed by the driving range of vehicles, longer paths require combinations of more than one station to refuel round-trip travel. A mixed-integer linear programming (MILP) version of the model has been formulated and published and could be used to obtain an optimal solution. However, because of the need for combinations of stations to satisfy demands, a realistic problem with a moderate size network and a reasonable number of candidate sites would be impractical to generate and solve with MILP methods. In this research, heuristic algorithms—specifically the greedy-adding, greedy-adding with substitution and genetic algorithm—are developed and applied to solve the FRLM problem. These algorithms are shown to be effective and efficient in solving complex FRLM problems. For case study purposes, the heuristic algorithms are applied to locate hydrogen-refueling stations in the state of Florida.
Transportation Research Board 94th Annual MeetingTransportation Research Board, 2015
A number of vehicle fleets around the world have transitioned to compressed natural gas (CNG), bu... more A number of vehicle fleets around the world have transitioned to compressed natural gas (CNG), but public refueling stations remains sparse away from fleet depots. Given the varied vehicle and route types of fleets, empirical data on their use of public refueling stations is important to understand, because like consumers, fleet drivers face range anxiety and their driving and refueling habits inform key assumptions important to station location. The authors surveyed 127 drivers of CNG fleet vehicles in Los Angeles at six stations across the metropolitan area. The key survey questions concerned the stops immediately before and after refueling, habituality of refueling away from base and fuel tank levels before refueling. The authors demonstrate that regardless of fleet or vehicle type, drivers deviate up to six minutes in order to refuel, and they also do not exhibit significant differences in fuel tank levels at the time of refueling. The authors also observe that 35% of fleet drivers surveyed indicated they were solely reliant upon away-from-base refueling for their operations, but there is variation between vehicle types. These findings demonstrate that fleet drivers do consider station locations away from their base when refueling, and they also indicate that assumptions made within facility location models with respect to fuel tank level and deviation thresholds do not necessarily have to consider the differences in vehicle or route type when employed at a metropolitan or regional scale.
China, like many developing countries, faces a difficult tradeoff between economic development an... more China, like many developing countries, faces a difficult tradeoff between economic development and environmental protection. Being the world’s largest producer and consumer of coal places a massive burden on China’s transportation and environmental systems. In 1989, energy shortages and runaway pollution prompted the World Bank and the Chinese State Planning Commission (SPC) to jointly undertake the China Coal Transport Study (CTS). At the time, China relied on coal for 73 percent of commercial energy, while coal accounted for 42 percent of rail freight. Rail transport, coal, and electricity were all suffering from debilitating shortages, which threatened China’s 10 percent annual economic growth. Meanwhile, SO2 and particulate levels were among the highest in the world, and CO2 emissions reached 11 percent of the world total — second after the United States.
ABSTRACT In recent years, transit planners are increasingly turning to simpler, faster, and more ... more ABSTRACT In recent years, transit planners are increasingly turning to simpler, faster, and more spatially detailed “sketch planning” or “direct demand” models for forecasting rail transit boardings. Planners use these models for preliminary review of corridors and analysis of station-area effects, instead of or prior to four-step regional travel demand models. This paper uses a sketch-planning model based on a multiple regression originally fitted to light-rail ridership data for 268 stations in nine U.S. cities, and applies it predictively to the Phoenix, Arizona light-rail starter line that opened in December, 2008. The independent variables in the regression model include station-specific trip generation and intermodal–access variables as well as system-wide variables measuring network structure, climate, and metropolitan-area factors. Here we compare the predictions we made before and after construction began to pre-construction Valley Metro Rail predictions and to the actual boardings data for the system’s first 6 months of operations. Depending on the assumed number of bus lines at each station, the predicted total weekday ridership ranged from 24,767 to 37,907 compared with the average of 33,698 for the first 6 months, while the correlation of predicted and observed station boardings ranged from r = 0.33 to 0.47. Sports venues, universities, end-of-line stations, and the number of bus lines serving each station appear to account for the major over- and under-predictions at the station level.
For location problems in which optimal locations can be at nodes or along arcs but no finite domi... more For location problems in which optimal locations can be at nodes or along arcs but no finite dominating set has been identified, researchers may desire a method for dispersing p additional discrete candidate sites along the m arcs of a network. This article develops and tests minimax and maximin models for solving this continuous network location problem, which we call the added‐node dispersion problem (ANDP). Adding nodes to an arc subdivides it into subarcs. The minimax model minimizes the maximum subarc length, while the maximin model maximizes the minimum subarc length. Like most worst‐case objectives, the minimax and maximin objectives are plagued by poorly behaved alternate optima. Therefore, a secondary MinSumMax objective is used to select the best‐dispersed alternate optima. We prove that equal spacing of added nodes along arcs is optimal to the MinSumMax objective. Using this fact we develop greedy heuristic algorithms that are simple, optimal, and efficient (O(mp)). Empirical results show how the maximum subarc, minimum subarc, and sum of longest subarcs change as the number of added nodes increases. Further empirical results show how using the ANDP to locate additional nodes can improve the solutions of another location problem. Using the p‐dispersion problem as a case study, we show how much adding ANDP sites to the network vertices improves the p‐dispersion objective function compared with (a) network vertices only and (b) vertices plus randomly added nodes. The ANDP can also be used by itself to disperse facilities such as stores, refueling stations, cell phone towers, or relay facilities along the arcs of a network, assuming that such facilities already exist at all nodes of the network.
Abstract: The diffusion of containerization has changed not only how general cargo is handled, bu... more Abstract: The diffusion of containerization has changed not only how general cargo is handled, but where. Using the Gini coefficient, we show that general cargo port traffic has become more concentrated from 1970 to 1988 because of four technological changes: ...
European Journal of Operational Research, Jul 1, 2010
This paper presents three heuristic algorithms that solve for the optimal locations for refueling... more This paper presents three heuristic algorithms that solve for the optimal locations for refueling stations for alternative-fuels, such as hydrogen, ethanol, biodiesel, natural gas, or electricity. The Flow-Refueling Location Model (FRLM) locates refueling stations to maximize the flow that can be refueled with a given number of facilities. The FRLM uses path-based demands, and because of the limitations imposed by the driving range of vehicles, longer paths require combinations of more than one station to refuel round-trip travel. A mixed-integer linear programming (MILP) version of the model has been formulated and published and could be used to obtain an optimal solution. However, because of the need for combinations of stations to satisfy demands, a realistic problem with a moderate size network and a reasonable number of candidate sites would be impractical to generate and solve with MILP methods. In this research, heuristic algorithms—specifically the greedy-adding, greedy-adding with substitution and genetic algorithm—are developed and applied to solve the FRLM problem. These algorithms are shown to be effective and efficient in solving complex FRLM problems. For case study purposes, the heuristic algorithms are applied to locate hydrogen-refueling stations in the state of Florida.
Transportation Research Board 94th Annual MeetingTransportation Research Board, 2015
A number of vehicle fleets around the world have transitioned to compressed natural gas (CNG), bu... more A number of vehicle fleets around the world have transitioned to compressed natural gas (CNG), but public refueling stations remains sparse away from fleet depots. Given the varied vehicle and route types of fleets, empirical data on their use of public refueling stations is important to understand, because like consumers, fleet drivers face range anxiety and their driving and refueling habits inform key assumptions important to station location. The authors surveyed 127 drivers of CNG fleet vehicles in Los Angeles at six stations across the metropolitan area. The key survey questions concerned the stops immediately before and after refueling, habituality of refueling away from base and fuel tank levels before refueling. The authors demonstrate that regardless of fleet or vehicle type, drivers deviate up to six minutes in order to refuel, and they also do not exhibit significant differences in fuel tank levels at the time of refueling. The authors also observe that 35% of fleet drivers surveyed indicated they were solely reliant upon away-from-base refueling for their operations, but there is variation between vehicle types. These findings demonstrate that fleet drivers do consider station locations away from their base when refueling, and they also indicate that assumptions made within facility location models with respect to fuel tank level and deviation thresholds do not necessarily have to consider the differences in vehicle or route type when employed at a metropolitan or regional scale.
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Papers by Michael Kuby