Efficient queue management.

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

Theo Raines in Tech & Innovation July 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'?

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.

About this Article -

This article was crafted using a human-AI hybrid and collaborative approach. AI assisted our team with initial drafting, research insights, identifying key questions, and image generation. Our human editors guided topic selection, defined the angle, structured the content, ensured factual accuracy and relevance, refined the tone, and conducted thorough editing to deliver helpful, high-quality information.See our About page for more information.

This article is based on research published under:

DOI-LINK: https://doi.org/10.48550/arXiv.2401.13812,

Title: A Characterization Of Optimal Queueing Regimes

Subject: econ.th cs.gt math.pr

Authors: Marco Scarsini, Eran Shmaya

Published: 24-01-2024

Everything You Need To Know

What is the main goal when designing an 'optimal' queuing regime?

The main goal of an 'optimal' queuing regime is to align individual decisions with the best possible outcome for everyone involved. This means the system must be both efficient and fair, avoiding strategic behaviors that could undermine its performance. Optimality involves balancing efficiency with the elimination of strategic behaviors to create a better experience for all users. This is achieved by considering arrival rates, service rates, and customer preferences to create a socially efficient outcome.

How does 'First-Come, First-Served' (FCFS) impact social optimality in a queue?

In a 'First-Come, First-Served' (FCFS) system, individuals tend to join queues more often than is socially optimal. This behavior is due to the negative externality that each new arrival creates, increasing the waiting time for everyone else. Naor's work in 1969 highlighted this issue. The challenge with FCFS is that it doesn't always consider the overall social benefit, often leading to a less efficient system because it doesn't account for the impact of individual decisions on the collective waiting experience.

What is the significance of not placing new arrivals at the back of the queue?

Hassin's research in 1985 demonstrated that queuing regimes that do not place new customers at the back of the queue can achieve optimality. When new customers are not added to the end of the line, their decision to join doesn't negatively impact those already waiting. This approach minimizes the negative externalities, potentially improving the overall efficiency and fairness of the queue. However, more recent research indicates that optimality can still be achieved even when new customers are sometimes placed at the back, provided the queue hasn't been longer in the past.

What are the different queuing regimes discussed, and how do they work?

The article mentions three queuing regimes: * 'First-Come, First-Served' (FCFS): Customers are served in the order they arrive. * 'Last-Come, First-Served' (LCFS): New arrivals are served immediately, potentially interrupting the service of the current customer. * 'Priority Slots': Customers are assigned slots with different priority levels, affecting their position in the queue. Each regime offers different ways to manage customer flow and wait times, and their effectiveness depends on the specific context and goals of the system.

How can we expect the experience of waiting to evolve in the future?

The future of waiting involves designing better queues by carefully balancing efficiency and fairness. As technology advances and research into queuing dynamics continues, there's an opportunity to implement innovative queuing regimes. These regimes should aim to transform the waiting experience into something more manageable and pleasant, by considering customer behavior and environmental conditions. The focus will be on creating systems that are not only efficient but also robust and adaptable to changes.