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Based on the theories of professional Campus Cafeteria, how do I solve crowding problems using high school rigs and technology?

[Outline]

I. Introduction

  1. Hook/ Attention Grabber

    • Introduce the shortcomings of the school cafeteria.

  2. Background Information

    • Provide statistical information to show that students in our school are not satisfied with the cafeteria (questionnaire).
    • Benefits of improvement [(Why research?)]:
      • Saves time in line
      • Increases student satisfaction
      • Increases faculty satisfaction
      • Reducing safety hazards
    • Potential risks of the present situation:
      • Students may crash with each other
      • Too much clutter leads to student dissatisfaction
      • Time is wasted (for study)

  3. Thesis Statement

    • This study aims to optimize the layout and flow of the cafeteria to effectively shorten students’ queuing time, increase the capacity and operational efficiency of the cafeteria, and ultimately enhance students’ dining satisfaction and the overall image of the school.

  4. Hypothesis

    • Potential reasons

Imbalance between supply and demand

  • Too many people eating
  • insufficient cafeteria capacity.
    Unreasonable process
  • unreasonable queuing line design
  • slow food pickup.
    Inadequate management
  • lack of effective diversion measures
  • chaotic dining order.
    Concentration of peaks
  • The meal times are too concentrated, leading to congestion during peak hours.

II. Body

Literature Review

  1. Common reasons
  2. Common Solutions
  3. Research gap

There has been relevant literature on queuing theory to solve congestion problems and also explains a variety of possible causes of congestion. For individual student behavior, there has been literature on decentralized ISM studies.

  • Scenario 1: This literature is based solely on standard cafeterias; our school’s cafeteria is very small, and we have expanded outdoors and staggered meals to barely accommodate all of our students.
  • Scenario 2: There is no literature that considers queuing space, the existing literature is based on cafeteria capacity. Our school’s queuing space happens to be the most crowded part of the school (based on assumptions).

Using Queueing Theory to identify Quantitative issues

  1. Introduction of Queueing Theory

    • Describe the main variables affecting cafeteria crowding:
      • The number of seats vs. total student population
      • Limited mealtime duration (typically 45-90 minutes)
      • Fixed number of windows (currently 3) and lunch staff
      • High influx of students at the same time due to class schedules

  2. Methods

    • Collect data over a week (Last morning class end to first afternoon class start) to model cafeteria dynamics:
      • Customer Arrival Interval: Measure the time intervals between student arrivals.
      • Service Time per Window: Record how long each window takes to serve students.
      • Window Count: Note that there are currently 3 serving windows.
Observing days: 4

  1. Model Variables

    • Main elements in the queueing model:
      • Student count, serving speed of lunch staff, fixed number of windows

  2. Discussion: Optimal Changes to Variables

    • Evaluate which variable adjustments yield the best crowding improvements.
    • Limitations:
      • Inconsistent queues due to varying food choices
      • Occasional events creating unpredictable flow
      • Space constraints limit seating expansion

Pedestrian Flow Simulation Model

  1. Data collection
    • From “Using Queueing Theory to identify Quantitative issues”
  1. People arrival curve
  2. window service time curve
    3*. Populations’ behaviors

  1. AnyLogic Simulation

    • Obtain an accurate floor plan of the cafeteria, including walls, columns, furniture, service windows… (if possible) or Taking photos and tracing them
    • Simulate lunchtime population activity.

  2. Conclusions about where the crowd areas are

    • Population density map to view.

  3. Limitations

    • Simplified models are not precise enough
    • Unpredictable distribution of people due to different cuisines
    • Short-term observations don’t mean anything

Possible Improvements of Cafeteria layout design

  1. To start with

    • Summarize the results of the simulation by identifying the major crowd areas in the cafeteria and the key factors contributing to this situation

  2. Optimizing Cafeteria layout design

    • Move the location of potentially problematic items (e.g., tables, chairs) and simulate again in AnyLogic to judge whether the crowding problem is solved or not

  3. Comparison

    • Move the location of potentially problematic items (e.g., tables, chairs) and simulate again in AnyLogic to judge whether the crowding problem is solved or not

  4. Limitations

    • In addition to demonstrating the effectiveness of the improvement program, its feasibility and limitations need be discussed:
    • Cost of implementation: Is the program budget realistic for the school?
    • Difficulty of retrofitting: Does the program require extensive retrofitting?
    • How long will the program take to implement?
    • Other Impacts: Will the program have an impact on the normal operation of the cafeteria?

Social Network Analysis ()

  1. Rationale

    • Students are not randomly seated in one seat, and students do not usually fill all the seats; generally groups of students will sit together and at a distance from another group

  2. Data collection from questionnaires (If possible) or observation

    • Who do you usually have lunch with?
    • How often do you two have lunch together, on a scale of 0-10?
    • Where do you usually sit?
    • When do you usually start eating?

  3. Analysis

    • Construct a relationship matrix that represents the social relationships between students.
    • The rows and columns of the matrix represent the students.
    • The elements of the matrix represent the strength of the relationship between the two students, e.g. 1 means friends, 0 means not friends.
    • Use Gephi’s layout algorithms, statistical metrics, and visualization tools to analyze and present the structure and characteristics of social networks.

  4. Result

    • Some small groups may sit in a fixed area and have fixed meal times, count all such groups, design specific dining areas for these groups, and divide these areas up.

  5. Limitations

    • Especially much bias, students fill out the questionnaire will have much bias, resulting in very inaccurate data, and similar to the school cafeteria which has become a systematic layout is very difficult to design as the above.

III. Conclusion

  1. Summary

    • Summarize all the key takeaways above

  2. Solutions

    • **Re-plan the location of the pickup, checkout and dining areas.
    • Add self-service pickup and self-service checkout equipment (Perhaps?).
    • **Streamline meal times (already been implemented by P3 / P4)
    • **Increase dining capacity
    • **Expand the cafeteria or add temporary dining areas (e.g. outdoor dining area).
    • **Improve service efficiency
    • Increase cafeteria staff to improve pick-up and cleaning speed.
    • Simplify the types of dishes to improve the speed of meal delivery.

IV. References

  • Include all sources cited in the paper.

V.Notes (insignificant)

  • Collected Data: Days to observe: 4
  • Calculations and Metrics:
    • 12+9+8
    • 48+26+32
    • 300
    • 150
    • 106
    • Introduction of queuing theory
    • 人，阿姨打饭时间，窗口数量（不太可能会变）结果
    • Disgusting（变哪个最有效）
    • Limitation（菜不一样人流不一样）（导致结果不够精确）（突然的活动）（Space）
      测4天

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