Vehicle Routing and Resource Allocation under Uncertainty: Efficient Optimization Models for Large-scale Real World Transportation and Health Care Problems - Brossura
Sinossi
In this book, we study optimization models for health care under uncertainty and resource constraints. In particular, we study two problems. The first problem is the multi-shift Vehicle Routing Problem (MSVRP) with overtime to meet around-the-clock demand. We use insertion to create the initial routes and then use tabu search to improve the routes. We show that our algorithm can find high-quality solutions for very large problems. The second problem is a multi-city resource allocation model to distribute the medical supplies in order to minimize the total number of fatalities in an infectious disease outbreak. We consider the problem with uncertainty in the initial number of cases and transmission rate, and build a two-stage stochastic programming model. To solve instances of realistic size we use a heuristic based on Benders decomposition. Finally, we use sample average approximation (SAA) to get confidence intervals on the optimal solution. We illustrate the use of the model and the solution technique in planning an emergency response to a hypothetic national smallpox outbreak. Computations show that the algorithm is efficient and can obtain near-optimal solution.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
L'autore
Yingtao Ren obtained his PhD in Operations Research and MS in Computer Science from University of Southern California. His research interests focus on developing efficient algorithms and optimization models for large scale real world problems in transportation, logistics and health care. He is currently employed as a research scientist in industry.
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Vehicle Routing and Resource Allocation under Uncertainty
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LAP LAMBERT Academic Publishing Sep 2011, 2011
ISBN 10: 3846512060
ISBN 13: 9783846512067
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this book, we study optimization models for health care under uncertainty and resource constraints. In particular, we study two problems. The first problem is the multi-shift Vehicle Routing Problem (MSVRP) with overtime to meet around-the-clock demand. We use insertion to create the initial routes and then use tabu search to improve the routes. We show that our algorithm can find high-quality solutions for very large problems. The second problem is a multi-city resource allocation model to distribute the medical supplies in order to minimize the total number of fatalities in an infectious disease outbreak. We consider the problem with uncertainty in the initial number of cases and transmission rate, and build a two-stage stochastic programming model. To solve instances of realistic size we use a heuristic based on Benders decomposition. Finally, we use sample average approximation (SAA) to get confidence intervals on the optimal solution. We illustrate the use of the model and the solution technique in planning an emergency response to a hypothetic national smallpox outbreak. Computations show that the algorithm is efficient and can obtain near-optimal solution. 120 pp. Englisch. Codice articolo 9783846512067
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Vehicle Routing and Resource Allocation under Uncertainty
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Vehicle Routing and Resource Allocation under Uncertainty
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Condizione: New. PRINT ON DEMAND pp. 120. Codice articolo 1898743946
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Vehicle Routing and Resource Allocation under Uncertainty
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LAP LAMBERT Academic Publishing, 2011
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ISBN 13: 9783846512067
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ren YingtaoYingtao Ren obtained his PhD in Operations Research and MS in Computer Science from University of Southern California. His research interests focus on developing efficient algorithms and optimization models for large scale. Codice articolo 5495745
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Vehicle Routing and Resource Allocation under Uncertainty
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LAP LAMBERT Academic Publishing Sep 2011, 2011
ISBN 10: 3846512060
ISBN 13: 9783846512067
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In this book, we study optimization models for health care under uncertainty and resource constraints. In particular, we study two problems. The first problem is the multi-shift Vehicle Routing Problem (MSVRP) with overtime to meet around-the-clock demand. We use insertion to create the initial routes and then use tabu search to improve the routes. We show that our algorithm can find high-quality solutions for very large problems. The second problem is a multi-city resource allocation model to distribute the medical supplies in order to minimize the total number of fatalities in an infectious disease outbreak. We consider the problem with uncertainty in the initial number of cases and transmission rate, and build a two-stage stochastic programming model. To solve instances of realistic size we use a heuristic based on Benders decomposition. Finally, we use sample average approximation (SAA) to get confidence intervals on the optimal solution. We illustrate the use of the model and the solution technique in planning an emergency response to a hypothetic national smallpox outbreak. Computations show that the algorithm is efficient and can obtain near-optimal solution.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 120 pp. Englisch. Codice articolo 9783846512067
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Vehicle Routing and Resource Allocation under Uncertainty : Efficient Optimization Models for Large-scale Real World Transportation and Health Care Problems
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LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3846512060
ISBN 13: 9783846512067
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this book, we study optimization models for health care under uncertainty and resource constraints. In particular, we study two problems. The first problem is the multi-shift Vehicle Routing Problem (MSVRP) with overtime to meet around-the-clock demand. We use insertion to create the initial routes and then use tabu search to improve the routes. We show that our algorithm can find high-quality solutions for very large problems. The second problem is a multi-city resource allocation model to distribute the medical supplies in order to minimize the total number of fatalities in an infectious disease outbreak. We consider the problem with uncertainty in the initial number of cases and transmission rate, and build a two-stage stochastic programming model. To solve instances of realistic size we use a heuristic based on Benders decomposition. Finally, we use sample average approximation (SAA) to get confidence intervals on the optimal solution. We illustrate the use of the model and the solution technique in planning an emergency response to a hypothetic national smallpox outbreak. Computations show that the algorithm is efficient and can obtain near-optimal solution. Codice articolo 9783846512067
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Vehicle Routing and Resource Allocation under Uncertainty | Efficient Optimization Models for Large-scale Real World Transportation and Health Care Problems
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LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3846512060
ISBN 13: 9783846512067
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Taschenbuch. Condizione: Neu. Vehicle Routing and Resource Allocation under Uncertainty | Efficient Optimization Models for Large-scale Real World Transportation and Health Care Problems | Yingtao Ren | Taschenbuch | 120 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783846512067 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Codice articolo 106782101
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