Publication Type

Journal Article

Version

submittedVersion

Publication Date

7-2025

Abstract

We study a multi-period joint capacity allocation and job assignment problem. The goal is to simultaneously allocate resources across J different supply nodes and assign jobs from I different demand origins to these J supply nodes, so as to maximize the reward for matching or minimize the cost of failure to match. We consider three features: (i) supply is replenishable after some random time, (ii) demand is random, and (iii) demand can wait and needs not be fully fulfilled immediately. Such problems emerge in many service management settings such as fleet re-positioning for car-sharing, and patient management in healthcare. We introduce a distributive decision rule that determines the proportion of jobs to be served by each supply node. We borrow ideas from the pipeline queues framework (Bandi and Loke 2018), which cannot be directly applied to our setting, and hence requires the development of new reformulation techniques. Our model has a convex reformulation and can be solved by a sequence of linear programs in practice. We test our model against state-of-the-art models focusing solely on the capacity allocation or job assignment decisions for the setting of nurse scheduling or patient overflow respectively. Our model performs strongly against the benchmarks, recording 1 − 15% reductions in costs and shorter computation times. Our model opens the door to consider new problems in platform operations and online services where a planner is able to partially influence the supply of services or resources.

Keywords

Programming, Convex optimization, Resource allocation

Discipline

Operations and Supply Chain Management | Operations Research, Systems Engineering and Industrial Engineering

Research Areas

Operations Management

Publication

Operations Research

ISSN

0030-364X

Identifier

10.1287/opre.2022.0255

Publisher

Institute for Operations Research and Management Sciences

Embargo Period

6-6-2025

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1287/opre.2022.0255

Download
Download Research Data

Share

COinS