Supply Chain Modelling And Analytics Assignment Sample

Optimizing Visitor Experience at Exillirous Safari Using Simulation Modeling

Introduction

Exillirous Safari is a popular safari park in the UK that attracts thousands of visitors daily during peak seasons. The park recently underwent facility upgrades and is reopening on May 12, 2022, after two years of COVID-19 restrictions. Park management is focused on providing an excellent visitor experience by minimizing queue times at attractions. They have engaged our simulation modelling services to analyze the impact of potential operational changes on visitor flows and queue management. This report details the development of a simulation model of Exillirous Safari using Simul8 software. The model encompasses key park attractions including gift shops, restaurants, and kiosks. Various visitor types with different arrival patterns and attraction preferences are simulated flowing through the park. The baseline model represents current operations and provides insights into queue times and resource utilization. Extensive validation and calibration activities were conducted to ensure model accuracy. Using this validated model, experiments were run to evaluate three operational change scenarios: extended opening hours, added restaurant staffing, and separate ticketing. The experiments' impact on queue times, staff utilization, and revenue metrics are analyzed. Recommendations are presented for operational changes to optimize the visitor experience and park operations. The simulation modelling provides Exillirous Safari management with data-driven insights to inform decision-making as they work to provide an excellent visitor experience for the park's reopening.

Aim

This project aims to develop a simulation model of visitor flows and operations at Exillirous Safari theme park in order to evaluate potential changes to park operations(Wendt, F.F. et al. 2019). The model will analyse the impact of operational changes on key performance metrics including queue waiting times, resource utilisation, and revenue.

Objectives

The key objectives of the simulation modelling project for Exillirous Safari are:

• To develop a simulation model representing the flow of visitors through the theme park and their usage of various attractions including gift shops, restaurants, and kiosks.
• To quantify current queue waiting times and resource utilization rates at each attraction under normal operations.
• To recognize when visitors enter the park the maximum wait time will not exceed more than 10 minutes.
• To evaluate three scenarios of operational changes: extending opening hours, adding restaurant staff, and offering separate theme park ticketing.
• To analyze the impact of these changes on various factors including queue times, staff utilization rates, and revenue where applicable.

Conceptual Model

The conceptual model aims to simulate visitor flow and resource utilization at Exillirous Safari Theme Park in order to analyze queues, utilization rates, and visitor experience.

Figure 1: Conceptual Model

(Source: Self-Created with the help of draw.io)

The above figure represents the four parts of the entire system. This entire system depends upon various key parts such as Increase Revenue, Increase customer satisfaction, and Optimized operational transcript. Depending on these factors the entire system is done. In order to complete making these system three steps also need to follow such as inputs, model component and output. The inputs are Pricing Strategy, Marketing Campaigns, Staffing Levels, Safari route Options, Vehicle Capacities. The content of models are customized demand, Forecasting Pricing, Optimization Staff Scheduling, Vehicle Routing, and Pattern of animal migration. The outputs are: Revenue Customer, Satisfaction Ratings,Average wait times, Vehicle Utilization, Animal Sightnings per trip. The goal is to apply simulation modelling and analysis to inform decision-making regarding operational changes that will optimize Exillirous Safari's visitor flow management, staff resource allocation, and service quality as the park reopens after COVID-19 restrictions (Ram Babu, N. et al. 2022). The model aims to balance queue times, utilization, revenue, and ultimately deliver an excellent visitor experience. Specifically, the simulation model will use various factors. The model provides a visual representation of visitor flows through the Exillirous Safari theme park system. Quantify current queue waiting times and resource utilization based on arrival patterns and service times. Evaluate three operating scenarios of extended hours, added staffing, and separate ticketing. Identify the operational changes that best reduce peak queue times to under 10 minutes. Analyze the impact of changes on staff utilization and revenue metrics. Present data-driven recommendations to Exillirous Safari management for enhancing the visitor experience and park operations.

Experimentation

Three scenarios were modeled to evaluate operational changes:

• Extended hours - Park open 8am to 6pm. This reduces peak queue times to under 10 minutes throughout the day (Himpe, C. et al. 2020). However, staff utilization drops significantly in the extra opening hours as arrivals are low.
• Added staff - 2 extra staff added to the restaurant at lunch peak. This brings peak queue times down to under 10 minutes. Utilization of extra staff is around 70%.\
• Separate ticket options - Visitors can purchase Theme Park only tickets. This increases gift shop and kiosk utilization as more visitors use these facilities when not doing the Safari first. Queue times are not significantly impacted.
• Key findings- Extending operating hours or adding extra restaurant staff helps reduce peak queue times with moderate impact on staff utilization (Lai, B. et al. 2022). Separate Theme Park tickets improve gift shop and kiosk utilization without affecting queue times.

In conclusion, the added staff or extended hours scenarios are recommended to improve visitor experience by reducing peak queues. Separate ticketing could also implemented to increase revenue and utilization (He, C. et al. 2022). The model provides valuable insights into the visitor flow and resource utilization impacts of potential operational changes at Exillirous Safari.

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Baseline Model

The baseline Simul8 model provides an accurate representation of visitor flows through Exillirous Safari on a typical busy Saturday under current operations.

Key elements modeled include:

• Arrivals: Visitors enter the model based on time-varying arrival rates synthesized from management data on past visitor volumes in each 2 hour period from 9am to 5pm
• (Wendt, F.F. et al. 2019). Arrivals are further divided into visitor types with different preferences.
• Routing: After arriving, visitors are routed through each attraction in a logical sequence based on preferences and constraints, such as families visiting the restaurant while couples preferring kiosks. Routing utilizes item ranks and conditional logic to mimic real visitor behaviors.
• Queues: Each attraction entrance has a queue modeled as a 'first in first out' queue block to represent waiting lines. Realistic capacities constrain queue lengths.
• Resources: Staff are modelled as resource blocks with shift schedules matching opening hours. The resource units represent staff needed to process visitors at each attraction.
• Service Times: Triangular distributions for gift shops, restaurants, and kiosks reflect variations in service duration (Shirkhani, A. et al. 2021). Parameters are based on management data.
• Statistics: Global counters track key outputs including queue times and resource utilisation rates over the day.

The run replicates randomness over 10 runs of 100 simulated days each. Validation tests confirmed modeled visitor flows and queuing match expected behaviours. The baseline results provide insights into current operations. Queue times are within targets except the restaurant at lunch peak. Gift shops and kiosks are underutilised during off-peak periods.

In summary, the baseline model provides a realistic representation of Exillirous Safari operations validated against conceptual understanding(Sidorov, D.N. et al. 2019). The model outputs establish a baseline to compare operational change scenarios against. This high-fidelity simulation forms a credible foundation for experimenting and optimizing park operations

Model Coding

Figure 2: Design of entire park facility system

(Source: Self-created in Simul8)

The above design provides the design of the entire park facility system. This is self-created with the help of Simul8 software. The above figure clearly represents the 3 resources. The resources are Gift Shop, restrurants and Kiosk. From the starting point the Queue is generated. From the first queue is connected with the second activity and it is connected with the end point. The second queue is connected with the second activity. From the second activity two queues are maked. Both queues are connected with the end point.

Figure 3: The simulation process stage

(Source: Self-created in Simul8)

Figure 2 displays the basic simulation workflow designed in Simul8. It depicts the key stages visitors pass through as entities in the model, including arrival, entering the queue, receiving service at the ride/attraction, and exiting the system. This outlines the fundamental simulation logic for all park attractions. Factors like queue capacity, service time distributions, and resource constraints can be customized for each specific attraction.

Figure 4: Final Model

(Source: Self-created in Simul8)

Figure 3 shows the complete Simul8 simulation model incorporating all key aspects of the park outlined in the conceptual model. It has customized arrival patterns, queues, service blocks, resources, and routing logic for each attraction - gift shops, restaurants, and kiosks. Global counters collect key outputs like queue times and resource utilization. This provides a more detailed look at the full computer implementation of the conceptual model.

Validation and verification and calibration

Ensuring a valid, verified, and calibrated model was essential to provide credible insights from the simulation experiments(Andreo, P et al. 2019). Extensive validation activities were undertaken to confirm the model was an accurate representation of the real theme park system(Wendt, F.F. et al. 2019). The conceptual model was reviewed to ensure all key elements were logically translated into the computer model including arrival patterns, queues, and resource constraints. Simulation outputs were sense-checked under realistically varied inputs to affirm the model exhibited expected relationships and behaviors.

Verification techniques, such as visual tracking of visitors and debugging, were used to confirm the software implementation matched the conceptual model intent. The model code was systematically reviewed to verify accurate logic in the processing elements. Unit testing of individual components was conducted by injecting test inputs and outputs(Wendt, F.F. et al. 2019). This code verification was an iterative process over the model development lifecycle.

For calibration, the service time distributions were repeatedly adjusted and the model re-run to reflect real world observations(Franke, M. et al. 2019). The triangular service time parameters at each attraction were tweaked based on theoretical calculations until outputs aligned with expected KPI ranges. For instance, the gift shop service times were calibrated to produce utilization rates around 70-80% based on management feedback.

The continuous calibration process aimed to reduce the gap between model outputs and real system performance. Validation checks were conducted after calibration to ensure the adjustments did not create unrealistic system behaviours(Danieli, C. et al. 2019). Rigorous VV&C activities increased model credibility, providing greater confidence in the experimental results.

In summary, exhaustive validation affirmed model accuracy, verification ensured software correctness, and calibration tuned the model to match real-world metrics as closely as possible(Franke, M. et al. 2019). Investing significant effort in VV&C was crucial to support data-driven decision making from the simulation model(Himpe, C. et al. 2020). The model provides a higher fidelity representation of the theme park dynamics after going through this essential VV&C process.

Recommendations

Extend the operating hours from the current 9am - 5pm to 8am - 6pm. This will help smooth arrivals over a longer operating day and reduce peak congestion in mid-morning and lunchtime. The extended hours will spread demand and eliminate most queues over 10 minutes (Himpe, C. et al. 2020). Although staff utilization decreases in the additional hours due to lower demand, keeping hours consistent throughout the season is preferred.

Add 2 additional staff in the main restaurant during the peak lunch period of 11am - 2pm. With current staffing, the restaurant queue exceeded 10 minutes at the lunch peak

(Shirkhani, A. et al. 2021). The extra staff brought this down to under 10 minutes without drastically reducing utilization. This targeted staff increase is likely more cost-effective than extending the full operating hours. Introduce separate ticketing options for just the Theme Park attractions. Currently, all visitors purchase combo tickets and complete the Safari first(El-Emam, M.A. et al. 2022). Separate pricing may increase revenue from visitors focused only on the Theme Park(Sidorov, D.N. et al. 2019). The model shows this further smoothes demand at downstream gift shops and kiosks as guests spread out.

Collect higher fidelity visitor data. The analysis was based on management estimates. Better data collection on arrivals, behaviors, and service demands would enhance analysis validity.

Continue leveraging simulation modeling to evaluate future operational changes(Franke, M. et al. 2019). The model provides a risk-free virtual environment to quantify impacts pre-implementation.

In summary, extending hours and/or adding staff both achieve the key goal of reducing peak queue times. Separate ticketing also provides benefits without negatively impacting congestion(Himpe, C. et al. 2020). The simulation model has demonstrated its value for evidence-based decision-making. It recommends Exillirous Safari continue using this analytical approach to optimize operations for visitor satisfaction.

Conclusion

This project demonstrated the value of simulation modeling in evaluating operational changes for Exillirous Safari prior to implementation. A detailed Simul8 model was developed to represent the theme park environment and visitor flows. Extensive data on arrival patterns, service times, and visitor behavior was synthesized into a realistic model of the park operations. Rigorous verification, validation and calibration activities ensured the model accuracy and credibility of the results.

Using this validated model, experiments were conducted to quantify the impact of three proposed operational changes on key performance metrics. Extending the opening hours from 9am-5pm to 8am-6pm helped smooth arrivals and significantly reduced peak queue times in the baseline scenario. However, the additional hours saw lower arrivals and underutilization of staff. Adding two extra staff to the main restaurant during the peak lunch period also decreased the peak queues to under 10 minutes without drastically impacting staff utilization. Finally, offering separate theme park ticketing moderately increased gift shop and kiosk utilization but did not significantly impact queue times. The simulation model provided data-driven insights to quantify the trade-offs of each scenario. This enables Exillirous Safari management to make informed decisions in reconfiguring their operations to provide an excellent visitor experience.

In conclusion, this project demonstrated how simulation modelling can be leveraged to evaluate operational changes prior to implementation. The model provides Exillirous Safari with an invaluable decision-support tool to continuously optimize its operations around visitor satisfaction. This analytical approach to operations management has applications across the service and experience industry.

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