Pharmacy duty scheduling problem

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Date

2016

Authors

Özpeynirci, Özgür

Journal Title

Journal ISSN

Volume Title

Publisher

Wiley

Open Access Color

Green Open Access

Yes

OpenAIRE Downloads

3

OpenAIRE Views

10

Publicly Funded

No
Impulse
Average
Influence
Average
Popularity
Top 10%

Research Projects

Journal Issue

Abstract

In this study, we define the pharmacy duty scheduling problem, which requires a subset of pharmacies to be on duty on national holidays, at weekends, and at nights, in order to be able to satisfy the emergency medicine needs. We model the pharmacy duty scheduling problem as a multiperiod p-median problem with special side constraints, and analyze the computational complexity. We propose a Tabu Search heuristic and develop lower bound (LB) algorithms. We test the performance of mathematical models, Tabu Search heuristic, and the LBs on randomly generated instances. We analyze the current system in. Izmir, the third largest city in Turkey, with a population of 3.5 million, and apply solution methods. Our results show that the proposed Tabu Search algorithm suggests improvements on the current system.

Description

Keywords

pharmacy duty scheduling, multiperiod p-median problem, Tabu search, Tabu Search Approach, Neighborhood Search, Station Location, Algorithm, Errors, Deterministic scheduling theory in operations research, tabu search, Case-oriented studies in operations research, multiperiod \(p\)-median problem, Approximation methods and heuristics in mathematical programming, pharmacy duty scheduling

Fields of Science

0211 other engineering and technologies, 02 engineering and technology

Citation

WoS Q

Q2

Scopus Q

Q1
OpenCitations Logo
OpenCitations Citation Count
7

Source

Internatıonal Transactıons in Operatıonal Research

Volume

23

Issue

3

Start Page

459

End Page

480
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Citations

CrossRef : 7

Scopus : 6

Captures

Mendeley Readers : 16

SCOPUS™ Citations

6

checked on Mar 25, 2026

Web of Science™ Citations

5

checked on Mar 25, 2026

Page Views

5

checked on Mar 25, 2026

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0.6732

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