A TWO-STAGE SOLUTION APPROACH FOR THE LARGE-SCALE HOME HEALTHCARE ROUTEING AND SCHEDULING PROBLEM

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Date

2017

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Southern African inst industrial Engineering

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Industrial Engineering
(1998)
Industrial Engineering is a field of engineering that develops and applies methods and techniques to design, implement, develop and improve systems comprising of humans, materials, machines, energy and funding. Our department was founded in 1998, and since then, has graduated hundreds of individuals who may compete nationally and internationally into professional life. Accredited by MÜDEK in 2014, our student-centered education continues. In addition to acquiring the knowledge necessary for every Industrial engineer, our students are able to gain professional experience in their desired fields of expertise with a wide array of elective courses, such as E-commerce and ERP, Reliability, Tabulation, or Industrial Engineering Applications in the Energy Sector. With dissertation projects fictionalized on solving real problems at real companies, our students gain experience in the sector, and a wide network of contacts. Our education is supported with ERASMUS programs. With the scientific studies of our competent academic staff published in internationally-renowned magazines, our department ranks with the bests among other universities. IESC, one of the most active student networks at our university, continues to organize extensive, and productive events every year.

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Abstract

The purpose of this study is to introduce a two-stage solution approach for a large-scale home healthcare routeing and scheduling problem (HHCRSP). In the first part of the two-stage solution approach, a cluster-assign algorithm is employed, based on the home location and the time to obtain feasible clusters. In the second stage, using these clusters, route construction heuristics start to create schedules and routes, taking the side constraints of the model into consideration. Using the novelty of this two-stage solution approach, higher diversification is achieved with a series of newly-developed cross movement strategies. The computational results show that our solution approach offers certain advantages, such as an increase in the efficient use of human resources, and a decrease in the working time of nurses.

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Erdem, Mehmet/0000-0003-4396-2149;

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15

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Q3

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Volume

28

Issue

4

Start Page

133

End Page

149

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