Optimal Partition for Multi-Type Queueing System

TL;DR

This paper investigates how to optimally partition servers and assign customer types in a multi-type queueing system to minimize waiting costs, revealing that strategic partitioning and assignment can significantly improve performance over simple heuristics.

Contribution

It introduces a novel framework for optimal server partitioning and customer assignment in heterogeneous queueing systems, including structural properties and efficient algorithms for the joint optimization problem.

Findings

Proper partitioning can arbitrarily reduce waiting costs.

Optimal customer assignment has a specific geometric structure.

Deterministic assignment is optimal under certain service time conditions.

Abstract

We study an optimal server partition and customer assignment problem for an uncapacitated FCFS queueing system with heterogeneous types of customers. Each type of customers is associated with a Poisson arrival, a certain service time distribution, and a unit waiting cost. The goal is to minimize the expected total waiting cost by partitioning the server into sub-queues, each with a smaller service capacity, and routing customer types probabilistically. First, we show that by properly partitioning the queue, it is possible to reduce the expected waiting costs by an arbitrarily large ratio. Then, we show that for any given server partition, the optimal customer assignment admits a certain geometric structure, enabling an efficient algorithm to find the optimal assignment. Such an optimal structure also applies when minimizing the expected sojourn time. Finally, we consider the joint partition-assignment optimization problem. The customer assignment under the optimal server partition admits a stronger structure. Specifically, if the first two moments of the service time distributions satisfy certain properties, it is optimal to deterministically assign customer types with consecutive service rates to the same sub-queue. This structure allows for more efficient algorithms. Overall, the common rule of thumb to partition customers into continuous segments ranked by service rates could be suboptimal, and our work is the first to comprehensively study the queue partition problem based on customer types.