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OR models in urban service facility location: A critical review of applications and future developments.

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Title: OR models in urban service facility location: A critical review of applications and future developments.
Authors: Farahani, Reza Zanjirani1, Fallah, Samira2, Ruiz, Rubén1,3 fastmaxr@gmail.com, Hosseini, Sara1, Asgari, Nasrin4
Source: European Journal of Operational Research. Jul2019, Vol. 276 Issue 1, p1-27. 27p.
Subjects: Service industries, Industrial location, Operations research, Cities & towns, Decision making
Abstract: Highlights • This survey focuses on the location of service facilities in urban areas. • 110 research papers across different journals and disciplines are studied. • Research is classified in terms of types of decisions, location space, main assumptions, input parameters, objective functions and constraints. • Results are also classified in terms of six different application categories. • Gaps, research opportunities and trends are identified within each category. Abstract Facility location models are well established in various application areas with more than a century of history in academia. Since the 1970s the trend has been shifting from manufacturing to service industries. Due to their nature, service industries are frequently located in or near urban areas that results in additional assumptions, objectives and constraints other than those in more traditional manufacturing location models. This survey focuses on the location of service facilities in urban areas. We studied 110 research papers across different journals and disciplines. We have analyzed these papers on two levels. On the first, we take an Operations Research perspective to investigate the papers in terms of types of decisions, location space, main assumptions, input parameters, objective functions and constraints. On the second level, we compare and contrast the papers in each of these applications categories: (a) Waste management systems (WMS), (b) Large-scale disaster (LSD), (c) Small-scale emergency (SSE), (d) General service and infrastructure (GSI), (e) Non-emergency healthcare systems (NEH) and (f) Transportation systems and their infrastructure (TSI). Each of these categories is critically analyzed in terms of application, assumptions, decision variables, input parameters, constraints, objective functions and solution techniques. Gaps, research opportunities and trends are identified within each category. Finally, some general lessons learned based on the practicality of the models is synthesized to suggest avenues of future research. [ABSTRACT FROM AUTHOR]
Copyright of European Journal of Operational Research is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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PubType: Academic Journal
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  Data: OR models in urban service facility location: A critical review of applications and future developments.
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  Data: <searchLink fieldCode="DE" term="%22Service+industries%22">Service industries</searchLink><br /><searchLink fieldCode="DE" term="%22Industrial+location%22">Industrial location</searchLink><br /><searchLink fieldCode="DE" term="%22Operations+research%22">Operations research</searchLink><br /><searchLink fieldCode="DE" term="%22Cities+%26+towns%22">Cities & towns</searchLink><br /><searchLink fieldCode="DE" term="%22Decision+making%22">Decision making</searchLink>
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  Data: Highlights • This survey focuses on the location of service facilities in urban areas. • 110 research papers across different journals and disciplines are studied. • Research is classified in terms of types of decisions, location space, main assumptions, input parameters, objective functions and constraints. • Results are also classified in terms of six different application categories. • Gaps, research opportunities and trends are identified within each category. Abstract Facility location models are well established in various application areas with more than a century of history in academia. Since the 1970s the trend has been shifting from manufacturing to service industries. Due to their nature, service industries are frequently located in or near urban areas that results in additional assumptions, objectives and constraints other than those in more traditional manufacturing location models. This survey focuses on the location of service facilities in urban areas. We studied 110 research papers across different journals and disciplines. We have analyzed these papers on two levels. On the first, we take an Operations Research perspective to investigate the papers in terms of types of decisions, location space, main assumptions, input parameters, objective functions and constraints. On the second level, we compare and contrast the papers in each of these applications categories: (a) Waste management systems (WMS), (b) Large-scale disaster (LSD), (c) Small-scale emergency (SSE), (d) General service and infrastructure (GSI), (e) Non-emergency healthcare systems (NEH) and (f) Transportation systems and their infrastructure (TSI). Each of these categories is critically analyzed in terms of application, assumptions, decision variables, input parameters, constraints, objective functions and solution techniques. Gaps, research opportunities and trends are identified within each category. Finally, some general lessons learned based on the practicality of the models is synthesized to suggest avenues of future research. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of European Journal of Operational Research is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.ejor.2018.07.036
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        Text: English
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      – SubjectFull: Industrial location
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      – SubjectFull: Operations research
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      – SubjectFull: Cities & towns
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      – SubjectFull: Decision making
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              Text: Jul2019
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