EVALUATION OF A PORT OPERATIONS MODEL USING THE 2012 WEST COAST PORT STRIKE AS DISRUPTION DATA

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1 10NCEE Tenth U.S. National Conference on Earthquake Engineering Frontiers of Earthquake Engineering July 21-25, 2014 Anchorage, Alaska EVALUATION OF A PORT OPERATIONS MODEL USING THE 2012 WEST COAST PORT STRIKE AS DISRUPTION DATA L. Ivey Burden ABSTRACT Seaports are an essential node in the transfer of goods into and out of the US, and they play an important role in the economy. However, history (Port of Kobe, Japan, 1995, Port Au Prince, Haiti, 2010) has shown that seaports are vulnerable to seismic hazards. This vulnerability and a method to calculate the risk associated with earthquake hazards in seaports was the focus of the NEES Grand Challenge Project: Seismic Risk Management for Port Systems. The study measured risk by creating a risk framework through which to estimate monetary losses resulting from earthquake disruption within a port system. The framework focused on calculating losses within the port and the aggregating effects that individual port component damage had on the system as a whole. The port system modeled was a hypothetical West Coast US port, and to date there have been no earthquake events that could be used as input into the framework to test the results produced. However, in November 2012, the Port of Los Angeles and the Port of Long Beach experienced an 8 day port strike that completely shut down many of the terminals. While this event is not an earthquake, it did cause a business interruption; a metric measured and accounted for within the aforementioned risk analysis framework. The work presented in this paper will conduct a preliminary investigation to examine the operations model used within the risk framework by comparing it to the 2012 port strike data for a single terminal. The operations model within the risk framework simulates the port operations by assigning incoming ships to specific berths and cranes within the port. If an earthquake (or other disruption) prevents ships from berthing at the port, the model keeps a record of all unprocessed ships and calculates business interruption losses from the reduced throughput of the port. This business interruption loss produce by the model can be compared to the actual business loss produced in the strike. In addition to testing the business interruption loss estimated, the port strike data will also offer insight into the method used to assign ships to berths since the reinitialization of the port after the disruption in the framework can be compared to the data available for the 2012 port strike. By comparing the two scenarios, the operational model used within the risk analysis can be evaluated, as it was developed to mimic actual port operator decisions. DOI: /D37W6763K

2 Evaluation of a Port Operations Model using the 2012 West Coast Port Strike as Disruption Data L. Ivey Burden 1 ABSTRACT Seaports are an essential node in the transfer of goods into and out of the US, and they play an important role in the economy. However, history (Port of Kobe, Japan, 1995, Port Au Prince, Haiti, 2010) has shown that seaports are vulnerable to seismic hazards. This vulnerability and a method to calculate the risk associated with earthquake hazards in seaports was the focus of the NEES Grand Challenge Project: Seismic Risk Management for Port Systems. The study measured risk by creating a risk framework through which to estimate monetary losses resulting from earthquake disruption within a port system. The framework focused on calculating losses within the port and the aggregating effects that individual port component damage had on the system as a whole. The port system modeled was a hypothetical West Coast US port, and to date there have been no earthquake events that could be used as input into the framework to test the results produced. However, in November 2012, the Port of Los Angeles and the Port of Long Beach experienced an 8 day port strike that completely shut down many of the terminals. While this event is not an earthquake, it did cause a business interruption; a metric measured and accounted for within the aforementioned risk analysis framework. The work presented in this paper will conduct a preliminary investigation to examine the operations model used within the risk framework by comparing it to the 2012 port strike data for a single terminal. The operations model within the risk framework simulates the port operations by assigning incoming ships to specific berths and cranes within the port. If an earthquake (or other disruption) prevents ships from berthing at the port, the model keeps a record of all unprocessed ships and calculates business interruption losses from the reduced throughput of the port. This business interruption loss produce by the model can be compared to the actual business loss produced in the strike. In addition to testing the business interruption loss estimated, the port strike data will also offer insight into the method used to assign ships to berths since the re-initialization of the port after the disruption in the framework can be compared to the data available for the 2012 port strike. By comparing the two scenarios, the operational model used within the risk analysis can be evaluated, as it was developed to mimic actual port operator decisions. Introduction History has shown through numerous cases (Port of Kobe, Japan 1995, Port Au Prince, Haiti 2010), that seaports are vulnerable to seismic hazards. This becomes a problem because seaports are essential nodes in the global transfer of goods, and downtime resulting from the disruption of container traffic can result in significant costs to shippers and port stakeholders. As a result, the vulnerability of seaports and a new, more-encompassing method to calculate risk at seaports was studied as part of the NEES Grand Challenge Project: Seismic Risk Management for Port Systems. Within this study, risk was associated with a monetary loss calculated from physical losses and business interruption losses within the port instead of at an arbitrarily defined hazard 1 Faculty, Dept. of Civil Engineering, University of Virginia, Charlottesville, VA Ivey-Burden L. Evaluation of a Port Operations Model using the 2012 West Coast Port Strike as Disruption Data. Proceedings of the 10 th National Conference in Earthquake Engineering, Earthquake Engineering Research Institute, Anchorage, AK, 2014.

3 level. By associating risk with a monetary value, port stakeholders are able to make more informed decisions regarding mitigation strategies and seismic upgrades [1]. The seismic risk framework created in the Seismic Risk Management for Port Systems project was calibrated specifically for earthquake occurrences, and port components commonly found in ports on the west coast of the United States. The risk analysis framework created calculates total port losses by estimating the physical damage occurring at a port subject to particular ground motion intensity and adding that to an estimation of an operational business loss grossed from the estimated value of container cargo that must be sent to another port because it exceeds the capacity of the earthquake-damaged port [2]. Since the completion of the project, there have been no earthquake events large enough to test the validity of the full model. However, the port strike that affected the Port of Long Beach and the Port of Los Angeles in late 2012 does offer the opportunity to comparatively examine the operational portion of the risk analysis. Background Operational Model The operational model used within the risk analysis framework uses an optimization-based heuristic scheduling technique to assign incoming ships to berths and cranes within a terminal. In current practice [3-5], berth scheduling and crane assignment is treated as a sequential problem. Terminal operators first determine berth assignment based on berthing durations of each vessel. Then, cranes are assigned to vessels depending on the number of ships docked simultaneously at each berth. Sequential practice of assignment can cause loading / unloading delays since the number of cranes for use at any given berth is finite. The optimization-based heuristic scheduling technique used in the risk analysis framework utilizes all of the information available to port operators (undamaged berths and cranes available) to simultaneously schedule berths and cranes, preventing the crane limitation [6]. The operational model used in this study is the Berth and Quay Crane Scheduling Program (BQCSP) [6]. The sub-optimal heuristic nature of this program is meant to mimic the postearthquake operational decision-making of terminal operators. Actual terminal operator assignment decisions attempt to maximize an objective function that balances the need to process containers quickly given available resources while avoiding excessive delay to any arriving vessels. These decisions are based on experience, judgment, the incoming arrival stream and several external factors. The complex nature of the problem means that a good, but not always the best decision will be made. Likewise, the decisions made by the BQCSP are also not always optimal. Within this technique, decisions are simulated regarding: (1) What arriving vessels may be turned away or will go another port (2) What times arriving vessels are berthed (3) Where they will be berthed within a particular terminal complex (4) Which cranes will be assigned to the vessels and when Depending on the outcome of the previously listed decisions, the BQCSP assigns post-disruption available berth space and cranes to each ship scheduled to arrive at the terminal. The program also uses a rolling time horizon that considers the schedule of arriving vessels several days into the future. Berth and crane assignments are updated daily based on the new information acquired from the rolling horizon. Within a risk analysis including an earthquake disruption, the operational model would

4 assign berths and cranes based on what portions of a terminal remained undamaged, and reassign ships in waiting as new sections of the terminal became available. During the 2012 port strike, entire terminals were shut down, therefore that event can be comparable to an earthquake event that damaged an entire terminal and then eight days later every berth was simultaneously repaired and available for use West Coast Port Strike The 2012 West Coast Port Strike took place from November 28 th through December 5 th, During that eight-day period, a strike by port clerical workers completely shut down seven of eight terminals in the Port of Los Angeles, and three of six terminals in the Port of Long Beach. During this period, it was estimated that the strike cost Southern California $8 billion, including lost wages and the value of cargo rerouted to other ports [7]. Evaluation of Port Model To test the port operations model, a simple comparison will be performed between one terminal affected by the port strike, and a terminal of a comparable length within the risk analysis framework. The input into the port operations model, like the actual data will require that the terminal examined is completely shut down for a period of eight days, and then reopened. Marine Exchange of Southern California Port Strike Data Vessel Arrival / Departure Data Shipping data from the time period of the port strike was retrieved from the Marine Exchange of Southern California. In the initial examination of the data, it appeared that several terminals that were closed sent waiting ships to operational terminals within the port to be serviced instead of sending them to another destination all together. In the event that a port sustained substantial damage in an actual earthquake, it would be expected that terminals would be universally damaged, but more likely than not, some cooperation resulting from force majeure would occur. To this end, the Long Beach Container Terminal (berths F6-F10) was selected as the test subject since during the disruption period it contained both ships sent to other terminals within the LA / Long Beach complex as well as ships that were sent to other ports entirely. Table 1 shows the data for ships arriving / departing the Long Beach Container Terminal (LBCT) from November 26 th December 16 th. The Marine Exchange of Southern California tracks arrivals, shifts, and departures in every terminal by ship. Therefore Table 1 is organized chronologically by ship arrival date. The first three columns of the table offer information on the vessel itself (number, name and length). The remaining columns detail the activities of the vessel within the port: describing the date and time of the vessel s arrival, shift, or departure, the berth (location) at which the vessel docked, the activity performed at that berth (D/L Discharge and Load, Strk Strike, and AB Awaiting Berth), and the overall location (Terminal and Port) within the Port of Los Angeles / Port of Long Beach system. Table 1. Marine Exchange of Southern California Port Strike Data

5 Vessel No Vessel Name Ship Length (ft.) Description Date Time Location Activity Terminal Port OOCL SOUTHAMPTON 323 Arrival 26-Nov-12 15:05 F8 D/L LBC LB OOCL SOUTHAMPTON 323 Departure 07-Dec-12 4:15 F8 LBC LB HANJIN CONSTANTZA Arrival 28-Nov-12 14:50 F8 Strk LBC LB HANJIN CONSTANTZA Departure 07-Dec-12 7:45 T136 TTI LB BALTIMORE BRIDGE Arrival 29-Nov-12 4:35 F7 Strk LBC LB BALTIMORE BRIDGE Departure 08-Dec-12 18:30 G232 ITS LB LORRAINE Arrival 29-Nov-12 10:45 F10 Strk LBC LB LORRAINE Departure 29-Nov-12 15:15 F10 LBC LB HANJIN ALGECIRAS Arrival 30-Nov-12 4:45 F6 Strk LBC LB HANJIN ALGECIRAS Departure 07-Dec-12 18:10 T138 TTI LB MAERSK MERLION Arrival 01-Dec-12 14:20 F10 Strk LBC LB MAERSK MERLION Departure 02-Dec-12 16:45 F10 LBC LB EVER ENVOY 300 Arrival 04-Dec-12 17:05 F9 Strk LBC LB EVER ENVOY 300 Departure 11-Dec-12 5: Seaside LA NYK LIBRA Arrival 04-Dec-12 6:10 F10 Strk LBC LB NYK LIBRA Departure 09-Dec-12 18: Yusen LA WANHE 280 Arrival 06-Dec-12 9:10 F6 AB LBC LB WANHE 280 Departure 10-Dec-12 7:35 T140 TTI LB OOCL NINGBO 323 Arrival 06-Dec-12 3:35 F14 AB LBC LB OOCL NINGBO 323 Shift 07-Dec-12 3:40 F8 D/L LBC LB OOCL NINGBO 323 Departure 11-Dec-12 17:50 F8 LBC LB OOCL TIANJIN Arrival 11-Dec-12 17:50 F8 D/L LBC LB OOCL TIANJIN Departure 16-Dec-12 17:35 F8 LBC LB As shown in the data, from November 26 th (2 days before the strike) to December 5 th (11 days after the strike) eleven ships total arrived and attempted to dock at one of the berths in the Long Beach Container Terminal. Of those 11 ships, two loaded and unloaded at LBCT, four were shifted to another terminal in the Port of Long Beach to be unloaded, two left the port for another destination, two went to the port of Los Angeles to be serviced, and one was shifted from waiting farther down in the non-cargo container portion of the Long Beach Container Terminal to be serviced once the strike was over. Business Interruption Losses The exact losses during the port strike are unknown. However it was estimated considering the shutdown of both ports, that losses to the national economy amounted to around 1 billion dollars per day [8]. Business interruption losses for the Long Beach Container Terminal (LBCT) during the 2012 port strike will be estimated by determining the amount of cargo that would have been unloaded / loaded were the strike to have never occurred. Twenty-foot equivalent units (TEUs) are the most common metric used for vessel capacity and terminal productivity. The unit is based on the volume of the 20-foot-long containers commonly loaded / unloaded from vessels. Therefore, for the LBCT the number of TEUs NOT processed will be considered business losses. Of the eleven vessels that came to the port during this time, two vessels (Lorraine and Maersk Merlion) arrived and immediately left the terminal for another destination. The total number of TEUs aboard both vessels is an obvious business loss. In addition, the two vessels that arrived at LBCT but were loaded / unloaded in the Port of Los Angeles (Ever Envoy and NYK Libra) will also be considered to have left for another destination, even though the Port of Long Beach and the Port of Los Angeles work within the same system. Commonly, specific companies own terminals. For instance, the Long Beach Container Terminal is owned by Long Beach Container Terminal Inc. By sending a vessel to another terminal, Long Beach Container Terminal Inc. does not receive payment for loading / unloading that vessel and therefore incurs a business loss. The four vessels that arrived at LBCT but were shifted to other terminals within the Port of Long Beach

6 (Hanjin Constantza, Baltimore Bridge, Hanjin Algeciras, and Wanhe) will also be considered business interruption losses since Long Beach Container Terminal Inc. would not have received payment for the unload / load of these vessels. The number of TEUs loaded and unloaded from each ship is not publically released information, and therefore no exact number of TEUs lost can be calculated. Instead, a TEU loss estimate will be calculated from the vessels that left the LBCT in the same manner as it is calculated in the risk analysis framework: using an estimated ratio of total TEU capacities for arriving ships to the total TEUs coming into and out of the port for a given month. In the risk analysis framework five months worth of shipping data was gathered from the Marine Exchange of Southern California and it was found that the mean ratio of TEUs into both ports (POLA and POLB) over the total TEU capacity of the ships serviced at both ports equaled 0.61, while the ratio of Out/ Total Capacity equaled The total number of TEUs loaded / unload per ship will be calculated with those ratios then multiplied by an estimated cost of $250 per TEU [9] to get a total business interruption loss for each vessel. Table 2 calculates the total business interruption loss per ship for the port strike data: Table 2. Calculation of Business Interruption Losses for Port Strike Data Vessel No Vessel Name TEU Capacity TEUs In TEUs Out Total TEUs BIL HANJIN CONSTANTZA $ 1,002, BALTIMORE BRIDGE $ 1,307, LORRAINE $ 808, HANJIN ALGECIRAS $ 1,002, MAERSK MERLION $ 1,414, EVER ENVOY $ 1,867, NYK LIBRA $ 1,822, WANHE $ 1,604, Total BIL = $ 10,830, BQCSP Operational Model Strike Simulation Vessel Arrival / Departure Data The port strike was simulated in the BQCSP operational model as an earthquake event with a repair requirement that shut down every berth and crane of an individual terminal for a period of eight days. The comparative terminal modeled was 2400 feet in length. This length is slightly shorter than the actual Long Beach Container Terminal, which is 2700 feet. This decision resulted from the way in which the operational model and the risk analysis framework are set up. Within the risk analysis framework, a berth section is defined as a 600-foot section. This section length is then divided into three 200-foot operational sections. These operational sections represent the berth length needed for one crane to load and unload cargo from a berthed vessel. Therefore, when defining the parameters for a hypothetical terminal within the risk analysis framework, the terminal length must consist of some number of berth sections, which means that the total length will be a multiple of 600. Table 3 displays the results of the BQCSP simulated port strike. The BQCSP program runs its scheduling program until it has determined that the port returns to normal operation after the disruption. This is the reason that the port strike simulation data ran for 30 total days, 22 of those days post-disruption. Table 3 is organized by scheduling activity each day with day one representing the start of the port strike. Each day provides information on the number of vessels

7 that attempted to dock at the port but left for another destination (vessels turned away) and the estimated TEUs lost due to that vessels departure. If the arriving vessel is berthed, that is indicated along with the total time that vessel spends at the port (total dwell) and any delays that might be incurred (total delay). The remaining columns in the table describe the utilization of berths and cranes within the terminal on a daily basis. Day Vessels Turned Away TEUs Lost Table 3. Berthed Ships BQCSP Port Strike Simulation Data Total Total TEUs Cranes Dwell Delay Handled Used (days) (days) Available Cranes Berth Used (feet) Available Berth (feet) In the port strike simulation seven total vessels left the terminal as a result of delays or the shut down. Four vessels left during the strike disruption itself, and three left as a result of long delays due to the backup of ships to be serviced after the disruption. Business Interruption Losses The BQCSP model uses a randomly generated vessel stream of actual vessels that have previously entered the Port of Long Beach and the Port of LA to model the number of TEUs that need to be handled by the port. The number of TEUs loaded / unloaded are calculated using the

8 TEU capacity of entering ships, and the total number of TEUs lost equals the sum of the TEUs on ships that were turned away from the port. Using the same estimation of cost per TEU lost ($250), the business interruption loss was calculated for the port strike simulation in Table 4: Table 4. Calculation of BIL for Port Strike Simulation Data Total Vessels Turned Away Total TEUs Lost Total BIL $12,307, Conclusions The main goal of this study was to use the BQCSP model to compare calculated business interruption losses and the modeling assumption used to describe actual port operations to the disruption caused by the 2012 west coast port strike. After gathering the port strike data and running a computer simulation the following conclusions can be made in the comparison of the two results: In comparison of business interruption losses, the simulation lost seven total vessels for a calculated loss of 12.3 million dollars. The Long Beach Container Terminal lost eight vessels for a total of 10.8 billion dollars. It seems as though the ships sampled in the BQCSP model had a larger TEU capacity on average than the ships that actually arrived at the Long Beach Container Terminal since fewer ships resulted in a larger business interruption loss. It would be interesting to further investigate this difference to see if a larger sample of random samples would result in a sum of TEU capacities closer to that of the simulation or of the actual port strike data. In comparison of the port operations, it seems as though the BQCSP model did a fairly accurate job of capturing the utilization of the berths and cranes within the simulated terminal. For days during the strike, the Long Beach Container Terminal berthed the one ship that had arrived before the strike and then sent away all of the other ships that arrived during the disruption. Of the two ships that arrived on the day after the completion of the strike, one was sent away and the other was held in waiting as the original ship waiting ship was serviced. This particular situation of TEU loss due to delay was also captured in the port strike simulation. In the simulation, two vessels arrived on the first day after the disruption. Both vessels were berthed and the cranes began to load / unload the vessels. During the period these vessels were being serviced, six more vessels arrived but at intervals that caused delays, but not exceptional delays at the port. Then on day 21 and 22, three additional vessels arrived. However, since the terminal had been operating at or near full utilization since the port strike, the delay that would be experienced by these three vessels would have been larger than the 3-day threshold set for the BQCSP and as a result, these vessels were sent to another destination. Future Work Refining the method by which the MXSOCAL data and the strike simulation are compared can further expand this work. On a large scale, the shifts and departures during the strike should be examined for terminals in addition to the Long Beach Container Terminal. These terminals could be modeled with separate simulations and compared, or data from each examined terminal could be combined into an average hypothetical terminal. In addition, it would be valuable to

9 conduct additional strike simulations to compare to the port strike terminal data. Multiple simulations would provide enough data to conduct a statistical analysis on the validity of the operational model as a modeling tool. On a smaller scale, it would also be beneficial to examine the affect that terminal length has on the operational models ability to capture the operations of terminal lengths that aren t a multiple of 600 feet. The two terminals compared in this example were 300 feet different in length, but still had similar ship arrival and business loss numbers. Since the average ship is around 300 ft. in length, it would be interesting to see if that extra footage could have actually accommodated a ship and if given the same number of operational cranes, if any of the three vessels that left due to delays could have been worked into the operations occurring after the port strike simulated disruption. References 1. Ivey, L.M., G.J. Rix, and S.D. Werner, Framework for Earthquake Risk Assessment for Container Ports. Transportation Reseach Record: Journal of the Transportation Research Board, 2010(2166). 2. Ivey Burden, L., Forecasting Earthquake Losses in Port Systems, in Civil and Environmental Engineering. 2012, Georgia Institute of Technology: Proquest Disserations and Theses. 3. Pachakis, D. and A.S. Kiremidjian, Estimation of Downtime-Related Revenue Losses in Seaports Following Scenario Earthquakes. Earthquake Spectra, (2): p Canonaco, P., et al., A queuing network model for the management of berth crane operations. Computers and Operations Research, (8): p Bierwirth, C. and F. Meisel, A survey of berth allocation and quay crane scheduling problems in container terminals. European Journal of Operations Research, (3): p Ak, A., Berth and Quay Crane Scheduling: Problems, Models, and Solution Methods, in Industrial Systems Engineering. 2008, Georgia Institute of Technology: Atlanta, GA. 7. Whitcomb, D. and S. Gorman. Deal reached to end L.A. port strike [cited 2013 September 15,]; Available from: 8. Riley, C. and C. Isidore. Deal Reached in California port strike [cited 2013 September 29]; Available from: 9. Seeds, N., Conversation about Delay Threshold and TEU Costs, G. Rix, 2011, Georgia Institute of Technology: Atlanta, GA.