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Research Articles

A New Model for Elderly Emotional Care Routing and Scheduling With Multi-Agency and the Combination of Nearby Services

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Pages 1111-1120 | Received 15 Jul 2021, Accepted 24 Feb 2022, Published online: 20 Apr 2022
 

Abstract

With the intensification of aging, more and more elderly people in China live alone and face the dilemma of less and less communication. However, an intrinsic requirement for the elderly to be accompanied and heard increases the demand for emotional care services. Hence, we focus on emotional care for the elderly and propose the multi-agency bi-objective elderly emotional care routing and scheduling model that considers both the travel and overtime costs of caregivers together with customers’ preferences for caregivers. We expand a single agency service mode to a multi-agency joint service mode to avoid a decline in customer satisfaction due to the fact that the single agency cannot meet all customers’ requirements in time. In addition, we design a merging method of nearby requirement points to save costs, which permits the same caregiver to provide services to customers in close geographic proximity at the same time on the premise that customers are willing to receive emotional care services with others. We add the constraint that every requirement cannot be rejected, ensuring that all requirements will be responded to. The results show that in the multi-agency joint service mode, all requirements are met without rejection. Compared with the single-agency service model, the proposed model can realize higher customer satisfaction at lower cost, which verified that the proposed multi-agency joint service mode can better meet the needs of a large number of elderly persons’ emotional care.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Key R&D Program of China (grant No. 2020YFB1711700) and the Fundamental Research Funds for the Central Universities (grant Nos. 2020CDJSK03ZH04 and 2021CDJKYJH022).

Notes on contributors

Peihan Wen

Peihan Wen is an associate professor at Chongqing University, China. He received a B.E. in Mechanical Engineering and a Ph.D. in Management Science and Engineering in 2004 and 2010, respectively, both from Tsinghua University, China. His current research interests are knowledge graphs, smart logistics, and aging problems.

Mo Chen

Mo Chen is a master’s degree student at Chongqing University, China. She received a B.E. in Logistics Engineering from Chongqing University in 2019. Her research interests include aging problems and elderly care.

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