Non-profit resource allocation and service scheduling with cross-subsidization and uncertain resource consumptions

•We formulate a chance-constrained model and three safe approximations for allocating for-profit and non-profit service in different resources.•We formulate an integrated resource allocation and service scheduling model for the above problem.•We conduct numerical studies on instances of for-profit a...

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Bibliographic Details
Published in:	Omega (Oxford) Vol. 99; p. 102191
Main Authors:	Lu, Mengshi, Nakao, Hideaki, Shen, Siqian, Zhao, Lin
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.03.2021
Subjects:	Allocation and scheduling Chance-constrained integer programming Non-profit operations research Safe approximations Allocation and scheduling Chance-constrained integer programming Non-profit operations research Safe approximations
ISSN:	0305-0483, 1873-5274
Online Access:	Get full text
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Summary:	•We formulate a chance-constrained model and three safe approximations for allocating for-profit and non-profit service in different resources.•We formulate an integrated resource allocation and service scheduling model for the above problem.•We conduct numerical studies on instances of for-profit and non-profit surgery planning to compare different models and approaches.•We analyze the impact of varying parameters and cross-subsidization on nonprofit operations. We consider a mixture of for-profit and non-profit requests that share multiple resources at random consumption rates. The revenue from fulfilling for-profit requests is used to cross-subsidize the cost of non-profit operations, and we aim to maximize the number of completed non-profit service requests. We consider two problems that respectively optimize resource allocation and service schedules, and employ chance constraints to restrict the probability of undesired outcomes such as resource over-utilization and service delay. For the allocation model, we propose three approximations of the chance-constrained program, and derive their variants to allow variable resource capacities. For the scheduling model, we derive a mixed-integer linear programming reformulation and develop a two-phase algorithm that separately decides allocation decisions and the start time of each service request. We conduct numerical studies on randomly generated instances of non-profit surgery planning to demonstrate the computational results of different models, and the impact of varying parameters and cross-subsidization on non-profit operations.
ISSN:	0305-0483 1873-5274
DOI:	10.1016/j.omega.2019.102191