Location Problems in Healthcare

Güneş, Evrim Didem; Melo, Teresa; Nickel, Stefan

doi:10.1007/978-3-030-32177-2_23

Cited by 20 publications

(19 citation statements)

References 113 publications

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“…Erlangen, Germany. 3 RWTH Aachen University, Pontdriesch 10-12, 52062 Aachen, Germany. 4 TU Kaiserslautern, Gottlieb-Daimler-Straße, 67663 Kaiserslautern, Germany.…”

Section: Availability Of Data and Materialsmentioning

confidence: 99%

Decision-Support Systems For Ambulatory Care, Including Pandemic Requirements: Using Mathematically Optimized Solutions

Leithäuser

Adelhütte

Braun

et al. 2021

Preprint

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Background: The healthcare sector poses many strategic, tactic and operational planning questions. Due to the historically grown structures, planning is often locally confined and much optimization potential is foregone. Methods: We implemented optimized decision-support systems for ambulatory care for four different real-world case studies that cover a variety of aspects in terms of planning scope and decision support tools. All are based on interactive cartographic representations and are being developed in cooperation with domain experts. The planning problems that we present are the problem of positioning centers for vaccination against Covid-19 (strategical) and emergency doctors (strategical/tactical), the out-of-hours pharmacy planning problem (tactical), and the route planning of patient transport services (operational). For each problem, we describe the planning question, give an overview of the mathematical model and present the implemented decision support application. Results: Mathematical optimization can be used to model and solve these planning problems. However, in order to convince decision-makers of an alternative solution structure, mathematical solutions must be comprehensible and tangible. Appealing and interactive decision-support tools can be used in practice to convince public health experts of the benefits of an alternative solution. The more strategic the problem and the less sensitive the data, the easier it is to put a tool into practice. Conclusions: Exploring solutions interactively is rarely supported in existing planning tools. However, in order to bring new innovative tools into productive use, many hurdles must be overcome.

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“…Erlangen, Germany. 3 RWTH Aachen University, Pontdriesch 10-12, 52062 Aachen, Germany. 4 TU Kaiserslautern, Gottlieb-Daimler-Straße, 67663 Kaiserslautern, Germany.…”

Section: Availability Of Data and Materialsmentioning

confidence: 99%

Decision-Support Systems For Ambulatory Care, Including Pandemic Requirements: Using Mathematically Optimized Solutions

Leithäuser

Adelhütte

Braun

et al. 2021

Preprint

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“…It uses simulation where scenarios correspond to different configurations of services. Several applications of facility location and extension are presented in these two surveys [18], [19],. Selecting locations for waste material in healthcare in [20] is another relevant application of location problems in healthcare.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Constraints (2) - (18) are similar except for variables having the index of scenarios of demand (Equation 7is replaced by Equation (21)). The new objective function (19) minimizes the expected transportation cost and the location of machines purchased overall scenarios. In (20) is enforced the probustness condition that is a measure that combines the minimization of the expected costs and the minimization of the worst-case cost or regret.…”

Section: Setsmentioning

confidence: 99%

Strategic territorial deployment of hospital pharmacy robots using a stochastic p-robust optimization approach

Franco

Augusto

Garaix

et al. 2018

2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)

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HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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“…Today there exists a vast literature on hierarchical location models, which can be traced back as early as to 1970s (see Narula, 1984Narula, (1984 for an earlier review). Those with some type of coverage objective have been studied mostly in health care systems (see for example, Afshari &Peng, 2014 andGüneş &Nickel, 2015 for reviews of such models), but there are also growing number of papers in other application areas. The more recent examples include facility location in banking (Min & Melachrinoudis, 2001), design of geo-location systems for search and rescue operations (Chan, Mahan, Chrissis, Drake, & Wang, 2008), response center location to combat effects of some chemical, biological, or nuclear accidents or attacks (Paul, Lunday, & Nurre, 2017), earthquake shelter location (Li, Zhao, Huang, & Hu, 2017), distribution center location in disaster management (Li, Ramshani, & Huang, 2018), court relocation (Teixeira, Bigotte, Repolho, & Antunes, 2019), and in last-mile delivery system design (Chauhan, Unnikrishnan, & Figliozzi, 2019).…”

Section: Introductionmentioning

confidence: 99%

A two-level facility location and sizing problem for maximal coverage

Karataş

Daşçı

2020

Computers & Industrial Engineering

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This paper presents a two-stage hierarchical location problem for systems where the lower level facilities act as the first points contact for the customers while the upper level facilities act as suppliers of the lower level facilities that either serve them or provide advanced services to customers. Furthermore, more recent and realistic coverage constructs such as gradual and cooperative covering are included in our setting. Although our problem can be applicable in various settings, the most fitting application is in wireless telecommunication networks to determine the location of base stations and mobile switching centers. We have developed two competing formulations for the problem, each of which involve nonlinear components that are difficult to deal with. We then develop their respective linearizations and tested their performances. These formulations are solved by commercial optimizers for a set of reasonably large problem instances and it is found that majority of the problems can be solved within a maximum of 10% optimality gap within a short time.

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Location Problems in Healthcare

Cited by 20 publications

References 113 publications

Decision-Support Systems For Ambulatory Care, Including Pandemic Requirements: Using Mathematically Optimized Solutions

Decision-Support Systems For Ambulatory Care, Including Pandemic Requirements: Using Mathematically Optimized Solutions

Strategic territorial deployment of hospital pharmacy robots using a stochastic p-robust optimization approach

A two-level facility location and sizing problem for maximal coverage

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