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Verlag: Creative Media Partners, LLC Mai 2025, 2025
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In den WarenkorbZustand: New. KlappentextrnrnThis research develops mathematical programming techniques to solve an intelligence, surveillance, and reconnaissance sensor assignment problem for USSTRATCOM. The problem as specifed is hypothesized to be difficult (i.e NP-HARD).
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Verlag: Creative Media Partners, LLC Okt 2012, 2012
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Taschenbuch. Zustand: Neu. Neuware - This research develops mathematical programming techniques to solve an intelligence, surveillance, and reconnaissance sensor assignment problem for USSTRATCOM. The problem as specifed is hypothesized to be difficult (i.e NP-HARD).With the smallest test cases, the true optimal solution is found using simple optimization techniques, but, due to intractability, the optimal solutions for larger test cases are not found using these same techniques. Instead, heuristic techniques are applied to several test cases in order to determine the best, robust methodologies to find true or near optimal solutions. Specifically, simulated annealing (SA) is tested for convergence properties across several different parameter settings. This research also utilizes local search techniques with simple exchange neighborhoods of various sizes. Mission prioritization is also examined via a weighted sum scalarization technique.
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In den WarenkorbPaperback. Zustand: new. Paperback. This research develops mathematical programming techniques to solve an intelligence, surveillance, and reconnaissance sensor assignment problem for USSTRATCOM. The problem as specifed is hypothesized to be difficult (i.e NP-HARD).With the smallest test cases, the true optimal solution is found using simple optimization techniques, but, due to intractability, the optimal solutions for larger test cases are not found using these same techniques. Instead, heuristic techniques are applied to several test cases in order to determine the best, robust methodologies to find true or near optimal solutions. Specifically, simulated annealing (SA) is tested for convergence properties across several different parameter settings. This research also utilizes local search techniques with simple exchange neighborhoods of various sizes. Mission prioritization is also examined via a weighted sum scalarization technique.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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In den WarenkorbHardcover. Zustand: new. Hardcover. This research develops mathematical programming techniques to solve an intelligence, surveillance, and reconnaissance sensor assignment problem for USSTRATCOM. The problem as specifed is hypothesized to be difficult (i.e NP-HARD).With the smallest test cases, the true optimal solution is found using simple optimization techniques, but, due to intractability, the optimal solutions for larger test cases are not found using these same techniques. Instead, heuristic techniques are applied to several test cases in order to determine the best, robust methodologies to find true or near optimal solutions. Specifically, simulated annealing (SA) is tested for convergence properties across several different parameter settings. This research also utilizes local search techniques with simple exchange neighborhoods of various sizes. Mission prioritization is also examined via a weighted sum scalarization technique.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.