A hybrid genetic algorithm for appointment scheduling in a health examination system. (20th October 2020)

• Record Type: Journal Article
• Authors: Ala, Ali; Torkayesh, Sajjad Ebadi; Torkayesh, Ali Ebadi; Iranizad, Atabak
• Is Part Of: International journal of value chain management. Volume 11:Number 4(2020)
• Page Start: 293
• Page End: 310
• Publication Date: 2020-10-20
• Subjects: health examination system -- HES -- appointment scheduling -- hybrid genetic algorithm -- HGA -- metaheuristic algorithms; Business logistics -- Periodicals; 658.7
• Languages: English
• ISSNs: 1741-5357

Abstract

A health examination system is a large system comprised of many units that include sectors or rooms, such as healthcare clinics, each of which requires unique tasks and experts to offer complete and timely healthcare. In general, every HES must accommodate a diverse population of individuals with unique medical histories and special behaviours. Access to and consideration of individuals' medical histories can reduce total exam times within a HES. Therefore, this study proposed a hybrid genetic algorithm that can be used to address the appointment scheduling in a HES to reduce the total preparation time of each room or sector, with a general aim to reduce total examination time. The proposed method is performed for 18 cases with different patient and room sizes in a health system. Results obtained all these cases showed higher accuracy and performance of the proposed method to the CPLEX solver in terms of the objective function and computational time.