Freight Transportation Resilience in Response to Supply Chain Disruptions (2019) / Chapter Skim
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Pages 56-69
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56 replace navigational buoys that were displaced in a flood or accident. Similarly, it would be helpful to increase the number of dredges and supporting equipment so that channels could be readily repaired and maintained.
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57 frequently, incorporating larger culverts, using grouted riprap, or rebuilding a bridge higher or with a wider span. The FHWA relief money can be used for a betterment if it can be shown that the project will save the agency money over time.
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58 Fostering public awareness of a collaboration and of what it can produce is a good strategy to weather changes in leadership. If the public has come to expect collaborative undertakings from a group of organizations, it will be difficult for new leadership to disband this group.
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59 Insufficient number of staff needed for the normalization of operations. This can be caused by internal constraints (e.g., inability to hire extra staff)
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60 From an institutional standpoint, a message that was repeated multiple times is that experience is a great teacher. Organizations should take advantage of smaller disruptions to incrementally improve the system and generate lessons learned.
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61 CHAPTER 5: ANALYSIS TOOLS AND MODELS FOR SUPPLY CHAIN RESILIENCE 5.1 INTRODUCTION An important component of anticipating and addressing the characteristics of supply chain disruptions is understanding freight flows and how they might respond to changes in network availability, and to quantify the costs versus benefits of proposed remedial actions. This is especially relevant where damage to the nation's transportation infrastructure is widespread and the loss of connectivity is protracted.
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62 5.2 TRADITIONAL TRIP BASED FREIGHT PLANNING MODELS For most regional planning authorities, the modeling of freight movements means developing a long-range (e.g., a 30-year) plan using a well-established "four-step" modeling approach geared to the estimation of 1)
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63 5.3 BEHAVIORALLY BASED, SUPPLY CHAIN MODELING OF NETWORK DISRUPTIONS While important for infrastructure utilization, land use planning, and traffic congestion studies, the traditional flowaggregated and trip-based approach to freight modeling has received extensive criticism for its lack of behavioral realism. Comparatively little effort has been given to incorporating the responses of the different freight actors involved in goods movement, including the shippers, carriers, receivers, warehouse operators and brokers of goods contracts.
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64 3. The fusion of a variety of data sources, running the gamut from remotely-collected digital datasets to expert interviews.
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65 5.4 CASE STUDY: THE PHARMACEUTICAL SUPPLY CHAIN FROM FLORIDA TO TEXAS This case study focused on the pharmaceutical supply chain from Miami, FL to Houston, TX (see Figure 4)
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66 Figure 4: Origin-Destination Pair for Pharmaceutical Supply Chain Scenario FreightSim is designed to be a policy-sensitive freight model that can be used to: Inform infrastructure investment decisions Evaluate congestion on Florida highways Test the effectiveness of statewide transportation policies on mobility and the economy Produce multimodal system performance measures for freight Evaluate the impacts of private sector decisions on the state transportation system Provide regional agencies with intercity freight travel options for regional planning purpose The model uses FAF Version 3 (FAF3) data along with other data such as Florida employment data as inputs into freight flow forecasting.
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67 The model utilizes pre-defined mode combinations to determine what modes are used to transport freight between each OD pair. These mode combinations are called "mode paths." For example, a "truck-air-truck mode path" means cargo is shipped by truck from its origin to a nearby airport, shipped by air to another airport near the destination, and shipped by truck from that airport to the destination.
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68 Interviews with industry stakeholders suggested that that just over half of the pharmaceuticals transported to Houston from Miami are transported by air. At first glance this seems to contradict the findings from the model base case.
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69 In freight modelling, a mode path is selected based on the logistics cost associated with the use of that link. Intuitively, mode paths with low logistics costs carry more volume compared to mode paths with higher costs.
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