Efficient queue management.

Queue Control: How to Make Waiting in Line More Fair and Efficient

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Theo Raines in Tech & Innovation May 2025 • 4 min read.

"Explore how different queuing strategies impact fairness and efficiency, and discover the optimal ways to manage customer wait times."


Waiting in line is a universal experience, often filled with frustration and anxiety. Whether it's at the grocery store, a theme park, or even in the digital world, queues are a necessary part of many systems. But what if there was a way to make these waiting times more bearable, even beneficial? Researchers have long studied the dynamics of queuing, seeking to understand how different strategies impact both the customer experience and the overall efficiency of the system.

The traditional approach to queuing assumes that customers behave randomly, entering or leaving the queue based on chance. However, in reality, people make strategic decisions about whether to join a line, and when to leave if the wait becomes too long. This strategic behavior can significantly impact the performance of a queue, leading to inefficiencies and dissatisfaction. Understanding these dynamics is crucial for designing better queuing systems.

Early studies, such as the seminal work by Naor (1969), revealed that under a first-come-first-served (FCFS) system, individuals tend to join queues more often than is socially optimal. This is because each new arrival increases the waiting time for everyone else, creating a negative externality. To address this, various interventions have been proposed, including capping queue lengths and imposing tolls. However, an alternative, explored by Hassin (1985), focuses on modifying the queuing regime itself.

What Makes a Queue 'Optimal'?

Efficient queue management.

The concept of an “optimal” queuing regime goes beyond simply minimizing average wait times. It involves creating a system where individual decisions align with the best possible outcome for everyone involved. This means ensuring that the system is not only efficient but also fair, preventing strategic behaviors that undermine its overall performance. Achieving this optimality requires a careful consideration of various factors, including arrival rates, service rates, and customer preferences.

One key idea is to avoid placing new arrivals at the back of the queue. Hassin (1985) demonstrated that regimes that don't add new customers to the end of the line can achieve optimality. This is because the last customer's decision doesn't create an externality for those ahead of them. However, more recent work has shown that optimality can be achieved even when new customers are sometimes placed at the back, provided the queue hasn't been longer in the past.

  • First-Come, First-Served (FCFS): The classic approach where customers are served in the order they arrive.
  • Last-Come, First-Served (LCFS): New arrivals are served immediately, potentially preempting the current customer.
  • Priority Slots: Customers are assigned slots with varying levels of priority, influencing their position in the queue.
Recent research has focused on characterizing the class of queuing regimes that achieve universal optimality, meaning they lead to socially efficient outcomes regardless of the specific parameters of the system. These studies aim to provide a framework for designing queues that are not only efficient but also robust to changes in customer behavior and environmental conditions.

The Future of Waiting: Designing Better Queues

As technology advances and our understanding of queuing dynamics deepens, the potential for creating better, more equitable waiting experiences continues to grow. By carefully considering the trade-offs between efficiency and fairness, and by implementing innovative queuing regimes, we can transform the often-dreaded experience of waiting in line into something more manageable, and perhaps even, dare we say, pleasant.

Everything You Need To Know

1

What does it mean for a queuing regime to be considered 'optimal'?

The concept of an 'optimal' queuing regime extends beyond simply reducing average wait times. It aims to establish a system where individual choices align with the most beneficial outcome for everyone involved. This entails creating a system that is both efficient and fair, thereby discouraging strategic behaviors that could undermine its overall effectiveness. Achieving this optimality necessitates a thorough evaluation of factors such as arrival rates, service rates, and customer preferences. In contrast to the traditional approach, it is important to account for non-random or strategic consumer behavior.

2

How does the First-Come, First-Served (FCFS) queue system work, and what are its implications?

The First-Come, First-Served (FCFS) system operates by serving customers in the precise order of their arrival. While seemingly straightforward and fair, under FCFS, individuals tend to join queues more often than is socially optimal because each new arrival increases the waiting time for everyone else, creating a negative externality. This can lead to longer overall wait times. Other queuing regimes, such as the Last-Come, First-Served (LCFS) or Priority Slots can address this inefficiency.

3

How do Priority Slots work in queue management, and what are the implications of using them?

Priority Slots assign customers slots with varying levels of priority, thereby influencing their position in the queue. This approach allows for differentiating service based on various criteria, such as urgency or membership status. The implications include potentially faster service for high-priority customers, but it can also lead to longer wait times for those with lower priority. It requires careful management to balance fairness and efficiency.

4

What strategies can be implemented to avoid placing new arrivals at the back of the queue, and why is this important?

One key strategy is to avoid always placing new arrivals at the back of the queue. Research indicates that queuing regimes that do not add new customers to the end of the line can achieve optimality. This is because the last customer's decision doesn't create a negative externality for those ahead of them. However, recent studies have found that optimality can be achieved even when new customers *are* sometimes placed at the back, provided the queue hasn't been longer in the past. The alternative queuing regimes include Last-Come, First-Served (LCFS) and Priority Slots.

5

Besides modifying the queuing regime itself, what other interventions can be used to improve fairness and efficiency in queues?

Queue lengths can be capped and tolls can be imposed to make waiting in line more fair and efficient. Capping queue lengths limits the number of customers allowed to join a queue, preventing it from becoming excessively long and discouraging strategic behaviors driven by long wait times. Imposing tolls, or fees for joining a queue, can deter less urgent customers and generate revenue that could be used to improve the overall queuing system. These measures help to manage demand and optimize the utilization of service resources.

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