B Simio Student Competition Problems

Twice each year Simio sponsors a simulation contest to challenge students across the world to solve real problems derived from challenges faced by Simio customers. This has rapidly grown be the largest such competition with about 4000 students from over almost 1000 teams competing each year. The problems not only challenge student model-building skills, but also require some creativity, project management, and even video production and presentation skills. Students find participation to be both interesting and valuable and winners often find themselves with attractive career choices.

If you would like to challenge yourself by competing, you can find out more at http://www.simio.com/academics/StudentCompetition (Figure B.1).

These Simio problems feature a wide variety of domains and challenges. If you would like an interesting project or practice problem, we have included some of the contest problem summaries here. If any of these pique your interest, you can find the full problem text at http://www.simio.com/academics/StudentCompetition/problem-archive.php.

Figure B.1: Challenge yourself with a Simio student competition problem.

B.1 Innovative Car Rentals

We are investigating a new startup business at airports that allow passengers to drop-off their car at our parking facility at the airport, and in addition to free parking they may receive rental income for their car while they are away. Their car is offered as a rental car to passengers flying into the airport. The basic business concept is outlined below:

• Departing passengers that arrive to the airport in a car that is pre-registered with our service may park their car for up to 3 weeks for free at our off-property parking/rental area as long as it is offered for rent in our rental pool.
• Cars entering the rental pool are cleaned for a fee paid by the owner of the car. If the car is rented it is re-cleaned at the end of the rental period at no cost to the owner; hence both a renter and the owner leave the airport in a clean car.
• Arriving passengers may use a mobile application to select from the available cars.
• Rental cars are classed as one of four types based on the model and year of the car. The rental price is set based on the category assigned, and 50% of the rental income received is paid to the owner of the car.

Because many of the parked cars will be rented we are able to offer parking to more customers than the available parking spaces that we have. The business strategy is to first pilot this system at a mid-size airport, and then rapidly expand to other airports once the concept is proven to be profitable. It’s very important that our pilot system be appropriately designed to maximize its chance of success to demonstrate the business model to potential investors. For this reason we want to use simulation to make critical design decisions with the layout of our system.

B.2 Simio Drilling Logistics

Simio Drilling Logistics (SDL) charters a number of offshore vessels to move material to and from various offshore drilling locations. The “as is” system dedicates a small number of vessels to service a set of offshore locations. Since the cost of an offshore rig going idle due to a lack of material is extremely high, SDL tends to procure vessels to meet maximum expectations to maximize drilling efficiency. Data indicates that there is much standby time at both ports and the offshore locations. SDL would like to improve vessel scheduling and potentially reduce the size of the offshore vessel fleet through operational improvements.

The first part of this problem is to model the “as-is” system with the current fleet of vessels dedicated to specific drilling locations. This model accounts for several different vessel types, and models the transport of a few different cargo items to the off shore rigs. The complexities of the system include the loading of the cargo onto the vessels and impact of weather and wave height on vessel transports and unloading. This “as-is” model will provide a baseline for evaluating improvement strategies for the system.

The second and most important part of this project is to develop and evaluate alternative strategies – such as pooling the vessels into a common fleet servicing all locations – to develop a “to-be” system that lowers the overall cost while maintaining the same high service levels. The project results will be judged both on the quality of the simulation models as well as the overall effectiveness/cost of the proposed “to-be” system.

B.3 Urgent Care Centers of Simio

Urgent Care Centers of Simio (UCCS) owns a number of urgent care centers across the country that provide patient care on a walk-in basis, typically during regular business hours as well as evenings and weekends. UCCS is generally equipped to treat conditions seen in primary care practices such as infections, flu, minor injuries, and simple fractures. UCCS are staffed by nurses, physicians and physician assistants, and specialists like an orthopedic specialist.

UCCS facilities include areas for patient registration, waiting, and triage as well as multiple exam / procedure rooms of various types. Patient demand varies not only by time of day and day of week, but also varies across their different centers. UCCS wants to determine the best general layout, staffing, room allocation, and other operating methodologies. UCCS would also like to evaluate how increasing patient incentives to pre-schedule for exams and other minor sicknesses could potentially reduce the staffing required.

Since it is desired to use the same model to optimize centers in many cities, the simulation model must be data driven to easily modify the patient demographics and experiment with the facility and staff configuration and optimization. The proposal must be “sold” to the UCCS board, so 3d animation and clarity of the results is particularly important.

B.4 Aerospace Manufacturing Problem

An aerospace manufacturer is evaluating planned changes to their final assembly systems.  Their process line has multiple work stations, each with a statement of work consisting of 10 to 20 aggregated tasks.  Each task has unique requirements for labor, tools and material handling.  The system is schedule driven, so any work not completed at the time the line pulses will be “traveled” downstream.  Production policies regarding this traveled work is one of the items to be evaluated during this project.  The manufacturing process is labor-intensive with a steep learning-curve, and work in process is costly.  Therefore, process improvement in the areas of labor productivity and reduction of work in process is critical.

The process currently has two established product types and the company plans to add a new product type to the process. The addition of a third production line is also driving the need to evaluate the production plan.

This manufacturer would like to evaluate the optimal production plan of going from the current state of two production lines, to a future state of two or three lines and a new throughput rate.   We will be evaluating different demand profiles, line allocation strategies, resource allocation strategies, and production policies such as how to address traveled work.

B.5 Latin American Supply Chain

A retail company that has existing locations in Latin America wishes to expand into the Caribbean and South America. It currently manufactures product in Asia. Demands vary by location and the market is volatile so flexibility and speed to market is essential. The company would like to evaluate creation of one or more distribution centers.

Should the company invest in a regional distribution center or fulfill orders direct from Asia manufacturing? If not direct, where should distribution centers be located taking into account future expansion strategy. Items to consider include the market growth rates in each country as well as the connectivity from each port for the countries.

The company also needs to evaluate different reorder policies and strategies for SKUs within the distribution center. Manufacturing production lead times and capacity restrictions as well as any port or fleet limitations must be respected. Costs for transportation, inventory holding, lost sales, order processing, and other components will be an important part of the decision.

B.6 Pulp and Paper Manufacturing Supply

An American group of pulp and paper manufacturers is increasingly aware of inefficiencies in obtaining wood as a raw material. Because they operate independently, very often logging trucks drive past one mill to deliver to a competitor mill, adding potentially avoidable transportation cost into the system. They are aware of a European consortium that controls wood deliveries to minimize logistics cost.

They want to evaluate the creation of a new consortium to manage wood deliveries to their mills.  The objective would be to minimize logistics cost.  There are 3 mills in an area, each consuming 4-6k tons of wood per day, running continuously.  Each mill involved has independent demand and maximum inventory, and some have offsite “drop yards” for additional inventory.  Wood is cut from in the region by small owner-operator logging companies.  Each independent logging operation has its own cutting and delivery capacity that varies seasonally.

The consortium would like a representation of the present system as well as the proposed system so they can evaluate the potential required investment, best operational parameters, and expected savings.

B.7 Global Currency Exchange

A major custodian bank in the global financial market provides currency exchange where they profit by charging the client a small percentage on each exchange. There are thousands of random, unpredictable transactions every day, requiring the bank to hold cash in each type of currency. At the end of each day the bank conducts a settlement with CLS Bank (Continously Linked Settlement Bank) to reset the quantities of each type of currency. CLS charges the bank a small percentage on this exchange. This confines the risk to the bank to a single day (known as intra-day liquidity risk). If the bank runs out of any type of currency, they can conduct a swap with one of their counterparties – essentially the same service provided by CLS, but it can occur anytime throughout the day. Swaps help mitigate risk, but they are expensive relative to CLS.

The bank is legally obligated to manage risk. If they are unable to support client transactions for any reason, it can cause a major disruption in the global financial market. Accordingly, they must prove to the government that they have sufficient cash on hand to avoid this situation across a range of stressing scenarios. Choosing the amount of each type of currency to keep on hand is a difficult problem. Students will be asked to simulate system activity (e.g., cash flows from transactions, swaps, and settlements) in order to find the profit maximizing quantities subject to acceptable risk. This will include analysis of revenue, cost, and risk. These analyses will be completed across a range of scenarios.

B.8 Sunrun Solar Panel Installation

Sunrun is the largest dedicated residential solar company in the United States. They tailor a solar system to meet a homeowner’s needs and handle all aspects of installation. Sunrun operates in 21 states and continues to grow every year.

For this project students are asked to consider the complexities of the “last mile” of solar panel installation. This process covers the actual movement of equipment, supplies and crews to a home (job site) and installing solar panels on the roof. Right now, there is a proposal to change the current standard to a new delivery process that can better handle the unexpected events that can delay or lengthen the installation. Senior management has requested an evaluation of the current process, comparison of the two scenarios, and recommendations for improving the installation process.

B.9 Seed Production

A seed production process spans various activities including: planting a given hybrid in the field, in-season operations, harvesting, and seed processing in the manufacturing facilities. In North America, the harvest season lasts for about 8 to 10 weeks starting middle to late August until early to middle of October each year. A set of fields is assigned to a manufacturing site for seed processing and packaging after the harvest is completed. The seed production facilities operate from mid September until April of the following year.

Given that they operate several seed production facilities with different product mix, the planning function needs to determine the production plan for each of these facilities keeping into account constraints such as product portfolio, complex bill of material, product routing through the facility, physical space and material handling systems, equipment configuration and efficiency, and workforce constraints among other items to ensure right seed is shipped to the right customer at the right time.

B.10 Megastore Distribution Center

Super Intensive Megastore with Integrated Operations (S.I.M.I.O.) utilizes cutting edge technology and advanced analytics to minimize cost. This is reflected in the level of sophistication of their distribution center operations. Real time information actively guides decision making. Verification, optimization, and automation are a part of daily life. Due to the complexity of the operation, it is difficult to predict how additional investment will function after implementation. Specifically, how should orders be prioritized and dispatched to minimize labor costs? The best way to answer system performance questions is to create a detailed digital twin of the system, simulate activity, and observe/quantify the outcomes.

Labor is the major cost driver and a constrained resource; the system can be divided along labor areas of: Put away (including vehicle constraints), Select, and Replenish. The focus of this problem will be put away. The primary goal will be to evaluate different dispatching methods to improve metrics like pallets per hour, utilization, cost and travel distance. We are looking for ways to achieve a specified target to help evaluate additional hardware to handle more of the inbound demand. The model must be implemented using data-driven techniques to make it easy to change parameters.

B.11 Regional Airport Planning

A regional airport is seeing an increase in passengers as the surrounding communities are developing and experiencing economic growth. However, this volume increase is causing the airport to be frequently plagued by congestion that could hinder the economic growth in the area. For this reason, the airport is evaluating improvement projects to help reduce the congestion and enhance passenger experience.

The airport is evaluating methods to reduce the congestion by targeting the time necessary for passengers to proceed through the airport (arrival, check-in, bag drop, security, arrive at gate). The airport has identified a few options to reduce passenger time in airport but is unsure which would have the most positive impact while factoring in cost and variability of passenger visits. The improvement options that are under consideration include improving and adding capacity to check in and security and/or adding a people mover within the terminal. The airport needs to assess these options and determine how to reduce passenger time in system in the most cost-effective manner.

In addition to the overcrowding occurring inside the airport, traffic congestion is becoming a problem at the terminal and surrounding roadways. The transit authority proposed adding separate bus routes to the airport in an effort to help alleviate this congestion. To incentive passengers to use the bus, the airport is considering expedited security just for bus riders. However, the airport is uncertain what the impact would be of implementing this proposal.

You are to develop a model of the current airport operations to serve as the baseline to compare the impact of the improvement options. Then evaluate the proposals (and suggest others) to provide an overall recommendation for the most cost-effective operations.

B.12 Miebach Distribution Center

The Miebach Distribution Center (MDC) is a warehouse that stores footwear and apparel items which are shipped as outgoing orders to customers. These orders range from “singles” which are single consumer purchases to multi-item orders. MDC is noticing an increase in orders as well as a diversification of order types. Warehouse planners and mangers are looking to improve picking operation strategy to meet their customer delivery goals. The planners and managers must determine how to balance the workload across the warehouse system, which includes taking into consideration the teams that work downstream of picking. The scope of this project starts with picking units from shelved storage and ends with packing and shipping the orders.

Due to the uptick of orders, the MDC is transitioning into wave picking management methodology or “waving” to collect the units from their storage locations. To wave the MDC warehouse, orders are grouped together, and the grouped orders’ units are split up by their corresponding warehouse zone storage location. The zone is picked by the workers and the units collected are moved to a staging area. Once all units from a wave reach the staging area, the wave is sent to packing and shipping. The wave is organized back into orders and shipped out.

The MDC is searching for recommendations for the best waving and picking strategy for managing their warehouse which optimizes labor utilization and minimizes missed customer delivery goals. The wave picking strategy should include the ideal size of a wave based on order attributes, unit locations, and acceptable picking receptacle. The criteria that places orders in the same wave should also be investigated. Additionally, the MDC would like to identify any warehouse re-zoning that would benefit the waving processes. The MDC is hoping for a set of rules that helps future formulation of waves.

B.13 Small Restaurant Operations

The Simio BBQ Smoke Pit is an up-and-coming local restaurant. It features a variety of BBQ smoked meats and classic sides. This makeshift cookout is nestled in an older, renovated building in a bustling downtown block. Due to size constraints, this is a carry-out only establishment. However, as Simio BBQ Smoke Pit continues to grow in popularity, customers are facing longer wait times due to product outages and a constrained labor force. To keep up with demand, the restaurant needs help determining what new policies to enact to resolve their service bottlenecks.

Due to the long smoking time required for the BBQ meats and lengthy cook time for some sides, the restaurant is struggling to keep a reasonable level of cooked food available. Having too little inventory will affect customer satisfaction. If food shortages occur too often, wait times could increase, causing customers to leave and losing potential business for the restaurant. On the other hand, creating excess inventory could accrue extra costs. The meat is expensive and excess uneaten food must be disposed of at the end of the day.

The challenge is to balance staffing and food production to maximize profits and customer satisfaction. The restaurant is looking to investigate customer arrivals and ordering patterns, resource requirements, and food production rates. Simio BBQ Smoke Pit desires the best strategy to replenish each of the different food items on their menu. This replenishment strategy not only affects when and how much food to cook, but also how to allocate the cooked portions between the meal assembly stations and the holding cabinets. Additionally, Simio BBQ would also like to know if the potential improvement of changing staffing levels or adding equipment would be worth the investment.

B.14 Supply Chain Planning Using DDMRP

The Simio Shelving Shop is a shelving manufacturer and wholesaler specializing in several types of shelving units with design variations. The shop is currently experiencing low order fill rates, affecting the shop’s bottom line. Management recently hired an outside consultant to provide recommendations for revamping the inventory and buffering system. The consultant recommended a new buffering and inventory paradigm, Demand Driven Materials Requirement Planning (DDMRP), to address the rampant stockout issue.

The factory currently uses static buffer levels, where all stations have a fixed amount of raw material buffered at their station, and the factory maintains a fixed number of each end item ready to ship. The current buffering method, combined with variations in lead time and quality throughout the factory and its suppliers, drives stockouts of finished goods and raw material. Management embraced the consultant’s recommendation to incorporate a DDMRP buffering solution into the factory because they are convinced that a dynamic buffering solution will improve a collection of selected Key Performance Indicators (KPIs), especially fill rate and average inventory cost. As a secondary objective, management also seeks better methods of monitoring risk in the buffer levels, which the DDMRP buffer profiles will provide.

The challenge is to set up dynamic DDMRP buffers in the factory. This will include leveraging pre-existing data from Sales, Quality, machines, and suppliers to first determine the locations of the buffers, then fine-tune the buffer parameters to improve the selected KPIs. After the buffers are integrated, management wants to predict the change in the factory’s KPIs. Additionally, management would like to reevaluate potential suppliers, which have varying lead times and product quality. This assessment will include recreating optimal buffers for the potential suppliers to determine the impact the supplier could have on the company’s fill rate and average inventory costs.