Study the utility of Network Analyst in solving resource displacement and resource allocation problem

The goal of this lab is to study the utility of Network Analyst in solving resource displacement and resource allocation problem. Resource displacement problem is used to solve the optimal path between locations of interest to the user. Resource allocation problem deals with service area optimization.

For the study to apply Esri’s network analysis algorithms, I have selected areas close to the UCLA campus. The objective is to determine an optimal path from a location on I-10 freeway that I travel every day to the UCLA’s south and north campus. These locations are shown on the map as stops 1, 2 and 3. The Solve tool in Network Analyst is used to find the optimal path between these locations. The optimal path is shown on the map, and it shows that the total travel distance is 8.1 mile and will take about 13 minutes to reach the UCLA campus from the starting location 1. The directions are shown in the map, and we see that it used I-405 in addition to I-10 to map the optimal route. Now, I introduce a polygon barrier at the intersection of I-10 and I-405 to evaluate its impact. I solve for an optimal path now, and it immediately shows that the drive time has increased and the distance travelled has also increased because the driver needs to avoid I-405 freeway. This is understandable, as freeways have higher travel speeds. But a careful observation reveals that the increase in distance is marginal – from 8.1 to 8.3 miles, but the travel time increased only by 2 minutes. This does not make much sense to me. We know that driving on a surface road in Los Angeles will in practice take much longer than just an additional 2 minutes because of junction lights and lower speeds. In addition, the optimal path does not factor in the traffic conditions. For heavy and congested traffic conditions, the travel times will be much higher. In addition, the Solver does not factor in the current road conditions in computing the travel time. For example, there could be rainy conditions and closure on certain roads, but these do not show up in the analysis. Perhaps, as GIS analysts, we can introduce these conditions in the analysis parameters of Network Analyst to determine a more realistic estimate of time and distance. As a regular traveler on these freeways on my way to UCLA to attend lectures and lab, my experience suggests that the usual travel times between these stops selected are usually more than 13 and 15 minutes suggested by Network Analyst Solver. To study impact of types of barriers, I also used point and line barriers to evaluate the impact on optimal travel time. The pattern was same in all the cases – the travel time and distance increased. But a realistic determination of optimal path must also account for traffic conditions, as these are dynamic or change all the time, the travel times will change with traffic conditions.

Another problem that I solved with the Network Analyst Solver is the service area problem. The goal is to find areas that can be serviced by certain amount of travel time or distance from a point of interest. For this study, I selected the intersection of I-10 and I-405. The objective is to find areas that can be serviced in 2, 3 and 5 minutes from the selected point of interest. The intersection point is shown on the map. The service area for 2, 3 and 5 minutes were computed using the Network Analyst Service Area solver. As expected, longer durations can serve larger area. But the critique used in the case of optimal path computation also applies here. The Solver as used here, does not factor in road conditions,barriers, closures and traffic conditions. All these factors affect travel times. For barrier impact study, I introduced a polygon barrier to see its effect on the service area. I used the Solver to compute the service area. The results show that the areas beyond the polygon barrier are now not being served. This is understandable. However, to make the results realistic, it is important that we consider the traffic and road conditions in our analysis. Because these conditions are dynamic and change with time, optimal service areas will be different at different times.

In summary, while Network Analyst Solver does provide an efficient way to solve for resource displace and resource allocation problems, there are external factors discussed above that also affect travel times and service areas. It is important that we keep these in mind while planning an optimal service area for resource allocation.