Budget Optimization and Allocation.:
Gespeichert in:
| 1. Verfasser: | |
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| Weitere Verfasser: | , |
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Sharjah :
Bentham Science Publishers,
2018.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | GA Population Selection. |
| Beschreibung: | 1 online resource (164 pages) |
| ISBN: | 1681087073 9781681087078 |
Internformat
MARC
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| 100 | 1 | |a Sahana, Sudip Kumar. | |
| 245 | 1 | 0 | |a Budget Optimization and Allocation. |
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| 300 | |a 1 online resource (164 pages) | ||
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| 505 | 0 | |a Intro; CONTENTS; FOREWORD; PREFACE; DEDICATION; SUMMARY; Introduction; 1.1. IMPORTANCE AND CHALLENGES OF BUDGET ALLOCATION IN NATIONAL AND GLOBAL ECONOMY; Military; Health Care; Education; 1.2. ADVANTAGES AND DISADVANTAGES OF BUDGET ALLOCATION; 1.2.1. Benefits of Budget Allocation; 1.2.2. Disadvantage of Budget Allocation; CONCLUDING REMARKS; CONSENT FOR PUBLICATION; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES; Literature Review; 2.1. TRADITIONAL BUDGET ALLOCATION TECHNIQUE; 2.1.1. Rank and Selection Technique; 2.1.2. Incremental Budgeting Technique. | |
| 505 | 8 | |a 2.1.3. Zero-based Budgeting Technique2.1.4. Ordinary Least Squares Technique (OLST); 2.1.5. Two-stage Least Squares Technique (2SLST); 2.2. LINEAR OPTIMIZATION; 2.3. NONLINEAR OPTIMIZATION; 2.4. METAHEURISTIC OPTIMIZATION; 2.4.1. Pareto Efficiency or Pareto Optimality; Marginal Conditions of Pareto Optimality; Pareto Efficiency in Social welfare; 2.4.2. Optimal Computing Budget Allocation (OCBA); 2.4.3. Genetic Algorithm (GA); 2.5. LITERATURE SURVEY; 2.6. PROBLEM STATEMENT; CONCLUDING REMARKS; CONSENT FOR PUBLICATION; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES; Research Methodology. | |
| 505 | 8 | |a 3.1. BUDGET ALLOCATION SCHEME/MODEL3.2. BUDGET OPTIMIZATION TECHNIQUE; 3.2.1. Proposed Evolutionary Computing based Framework for Budget Allocation and Optimization; 3.2.1.1. Mathematical Finance; 3.2.1.2. Evolutionary Computing Approach; Pseudo code for the Crossover Process; 3.3. BUDGET ALLOCATION TECHNIQUE; CONCLUDING REMARKS; CONSENT FOR PUBLICATION; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES; Result and Discussion; 4.1. TEST CASE 1: GROWTH RATE CALCULATION; 4.2. TEST CASE 2: PERCENT GROWTH RATE; 4.3. TEST CASE 3: MEAN AND STANDARD DEVIATION TECHNIQUE. | |
| 505 | 8 | |a 4.4. OPTIMIZATION TECHNIQUE 1: OCBA TECHNIQUE4.5. OPTIMIZATION TECHNIQUE 2: EA TECHNIQUE; 4.6. OPTIMIZATION TECHNIQUE 3: GA OPTIMIZATION; 4.7. BUDGET ALLOCATION TECHNIQUE; 4.7.1. Scheme 1: National Council of Education Research and Training (NCERT); 4.7.2. Scheme 2: Kendriya Vidyalaya Sangathan (KVS); 4.7.3. Scheme 3: Central Tibetan School Society Administration; 4.7.4. Scheme 4: Scheme for Setting Up 6000 Model Schools; 4.7.5. Scheme 5: Rashtriya Madhyamik Shiksha Abhiyan (RMSA); 4.7.6. Scheme 6: Navodaya Vidyalaya Samiti (NVS); 4.8. OUTPUT OF BUDGET ALLOCATION; CONCLUDING REMARKS. | |
| 505 | 8 | |a CONSENT FOR PUBLICATIONCONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES; APPENDIX A; ALLOCATION OCBA; Public Class Allocation_OCBA; Applet Window Code for Simulation; Simulation Pane Code for simulation; OCBA and EA Simulation Run; Optimal Computing Budget Allocation Simulation; Equal Allocation (EA) Simulation; Graph Generation; APPENDIX B; SIMULATION OF MEAN AND STANDARD DEVIATION; Calculation of Growth Rate; Department Wise Budget Allocation; Percentage Growth Rate Calculation; APPENDIX C; BUDGET ALLOCATION USING GENETIC ALGORITHM APPROACH FITNESS CALCULATION; GA Algorithm. | |
| 500 | |a GA Population Selection. | ||
| 650 | 0 | |a Mathematical optimization. |0 http://id.loc.gov/authorities/subjects/sh85082127 | |
| 650 | 6 | |a Optimisation mathématique. | |
| 650 | 7 | |a Mathematical optimization |2 fast | |
| 700 | 1 | |a Khowas, Moumita. | |
| 700 | 1 | |a Sinha, Keshav. | |
| 776 | 0 | 8 | |i Print version: |a Sahana, Sudip Kumar. |t Budget Optimization and Allocation: an Evolutionary Computing Based Model. |d Sharjah : Bentham Science Publishers, ©2018 |z 9781681087085 |
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Datensatz im Suchindex
| DE-BY-FWS_katkey | ZDB-4-EBA-on1048920126 |
|---|---|
| _version_ | 1816882468673814528 |
| adam_text | |
| any_adam_object | |
| author | Sahana, Sudip Kumar |
| author2 | Khowas, Moumita Sinha, Keshav |
| author2_role | |
| author2_variant | m k mk k s ks |
| author_facet | Sahana, Sudip Kumar Khowas, Moumita Sinha, Keshav |
| author_role | |
| author_sort | Sahana, Sudip Kumar |
| author_variant | s k s sk sks |
| building | Verbundindex |
| bvnumber | localFWS |
| callnumber-first | Q - Science |
| callnumber-label | QA402 |
| callnumber-raw | QA402.5 |
| callnumber-search | QA402.5 |
| callnumber-sort | QA 3402.5 |
| callnumber-subject | QA - Mathematics |
| collection | ZDB-4-EBA |
| contents | Intro; CONTENTS; FOREWORD; PREFACE; DEDICATION; SUMMARY; Introduction; 1.1. IMPORTANCE AND CHALLENGES OF BUDGET ALLOCATION IN NATIONAL AND GLOBAL ECONOMY; Military; Health Care; Education; 1.2. ADVANTAGES AND DISADVANTAGES OF BUDGET ALLOCATION; 1.2.1. Benefits of Budget Allocation; 1.2.2. Disadvantage of Budget Allocation; CONCLUDING REMARKS; CONSENT FOR PUBLICATION; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES; Literature Review; 2.1. TRADITIONAL BUDGET ALLOCATION TECHNIQUE; 2.1.1. Rank and Selection Technique; 2.1.2. Incremental Budgeting Technique. 2.1.3. Zero-based Budgeting Technique2.1.4. Ordinary Least Squares Technique (OLST); 2.1.5. Two-stage Least Squares Technique (2SLST); 2.2. LINEAR OPTIMIZATION; 2.3. NONLINEAR OPTIMIZATION; 2.4. METAHEURISTIC OPTIMIZATION; 2.4.1. Pareto Efficiency or Pareto Optimality; Marginal Conditions of Pareto Optimality; Pareto Efficiency in Social welfare; 2.4.2. Optimal Computing Budget Allocation (OCBA); 2.4.3. Genetic Algorithm (GA); 2.5. LITERATURE SURVEY; 2.6. PROBLEM STATEMENT; CONCLUDING REMARKS; CONSENT FOR PUBLICATION; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES; Research Methodology. 3.1. BUDGET ALLOCATION SCHEME/MODEL3.2. BUDGET OPTIMIZATION TECHNIQUE; 3.2.1. Proposed Evolutionary Computing based Framework for Budget Allocation and Optimization; 3.2.1.1. Mathematical Finance; 3.2.1.2. Evolutionary Computing Approach; Pseudo code for the Crossover Process; 3.3. BUDGET ALLOCATION TECHNIQUE; CONCLUDING REMARKS; CONSENT FOR PUBLICATION; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES; Result and Discussion; 4.1. TEST CASE 1: GROWTH RATE CALCULATION; 4.2. TEST CASE 2: PERCENT GROWTH RATE; 4.3. TEST CASE 3: MEAN AND STANDARD DEVIATION TECHNIQUE. 4.4. OPTIMIZATION TECHNIQUE 1: OCBA TECHNIQUE4.5. OPTIMIZATION TECHNIQUE 2: EA TECHNIQUE; 4.6. OPTIMIZATION TECHNIQUE 3: GA OPTIMIZATION; 4.7. BUDGET ALLOCATION TECHNIQUE; 4.7.1. Scheme 1: National Council of Education Research and Training (NCERT); 4.7.2. Scheme 2: Kendriya Vidyalaya Sangathan (KVS); 4.7.3. Scheme 3: Central Tibetan School Society Administration; 4.7.4. Scheme 4: Scheme for Setting Up 6000 Model Schools; 4.7.5. Scheme 5: Rashtriya Madhyamik Shiksha Abhiyan (RMSA); 4.7.6. Scheme 6: Navodaya Vidyalaya Samiti (NVS); 4.8. OUTPUT OF BUDGET ALLOCATION; CONCLUDING REMARKS. CONSENT FOR PUBLICATIONCONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES; APPENDIX A; ALLOCATION OCBA; Public Class Allocation_OCBA; Applet Window Code for Simulation; Simulation Pane Code for simulation; OCBA and EA Simulation Run; Optimal Computing Budget Allocation Simulation; Equal Allocation (EA) Simulation; Graph Generation; APPENDIX B; SIMULATION OF MEAN AND STANDARD DEVIATION; Calculation of Growth Rate; Department Wise Budget Allocation; Percentage Growth Rate Calculation; APPENDIX C; BUDGET ALLOCATION USING GENETIC ALGORITHM APPROACH FITNESS CALCULATION; GA Algorithm. |
| ctrlnum | (OCoLC)1048920126 |
| dewey-full | 519.3 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.3 |
| dewey-search | 519.3 |
| dewey-sort | 3519.3 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| format | Electronic eBook |
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| id | ZDB-4-EBA-on1048920126 |
| illustrated | Not Illustrated |
| indexdate | 2024-11-27T13:29:06Z |
| institution | BVB |
| isbn | 1681087073 9781681087078 |
| language | English |
| oclc_num | 1048920126 |
| open_access_boolean | |
| owner | MAIN DE-863 DE-BY-FWS |
| owner_facet | MAIN DE-863 DE-BY-FWS |
| physical | 1 online resource (164 pages) |
| psigel | ZDB-4-EBA |
| publishDate | 2018 |
| publishDateSearch | 2018 |
| publishDateSort | 2018 |
| publisher | Bentham Science Publishers, |
| record_format | marc |
| spelling | Sahana, Sudip Kumar. Budget Optimization and Allocation. Sharjah : Bentham Science Publishers, 2018. 1 online resource (164 pages) text txt rdacontent computer c rdamedia online resource cr rdacarrier Print version record. Intro; CONTENTS; FOREWORD; PREFACE; DEDICATION; SUMMARY; Introduction; 1.1. IMPORTANCE AND CHALLENGES OF BUDGET ALLOCATION IN NATIONAL AND GLOBAL ECONOMY; Military; Health Care; Education; 1.2. ADVANTAGES AND DISADVANTAGES OF BUDGET ALLOCATION; 1.2.1. Benefits of Budget Allocation; 1.2.2. Disadvantage of Budget Allocation; CONCLUDING REMARKS; CONSENT FOR PUBLICATION; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES; Literature Review; 2.1. TRADITIONAL BUDGET ALLOCATION TECHNIQUE; 2.1.1. Rank and Selection Technique; 2.1.2. Incremental Budgeting Technique. 2.1.3. Zero-based Budgeting Technique2.1.4. Ordinary Least Squares Technique (OLST); 2.1.5. Two-stage Least Squares Technique (2SLST); 2.2. LINEAR OPTIMIZATION; 2.3. NONLINEAR OPTIMIZATION; 2.4. METAHEURISTIC OPTIMIZATION; 2.4.1. Pareto Efficiency or Pareto Optimality; Marginal Conditions of Pareto Optimality; Pareto Efficiency in Social welfare; 2.4.2. Optimal Computing Budget Allocation (OCBA); 2.4.3. Genetic Algorithm (GA); 2.5. LITERATURE SURVEY; 2.6. PROBLEM STATEMENT; CONCLUDING REMARKS; CONSENT FOR PUBLICATION; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES; Research Methodology. 3.1. BUDGET ALLOCATION SCHEME/MODEL3.2. BUDGET OPTIMIZATION TECHNIQUE; 3.2.1. Proposed Evolutionary Computing based Framework for Budget Allocation and Optimization; 3.2.1.1. Mathematical Finance; 3.2.1.2. Evolutionary Computing Approach; Pseudo code for the Crossover Process; 3.3. BUDGET ALLOCATION TECHNIQUE; CONCLUDING REMARKS; CONSENT FOR PUBLICATION; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES; Result and Discussion; 4.1. TEST CASE 1: GROWTH RATE CALCULATION; 4.2. TEST CASE 2: PERCENT GROWTH RATE; 4.3. TEST CASE 3: MEAN AND STANDARD DEVIATION TECHNIQUE. 4.4. OPTIMIZATION TECHNIQUE 1: OCBA TECHNIQUE4.5. OPTIMIZATION TECHNIQUE 2: EA TECHNIQUE; 4.6. OPTIMIZATION TECHNIQUE 3: GA OPTIMIZATION; 4.7. BUDGET ALLOCATION TECHNIQUE; 4.7.1. Scheme 1: National Council of Education Research and Training (NCERT); 4.7.2. Scheme 2: Kendriya Vidyalaya Sangathan (KVS); 4.7.3. Scheme 3: Central Tibetan School Society Administration; 4.7.4. Scheme 4: Scheme for Setting Up 6000 Model Schools; 4.7.5. Scheme 5: Rashtriya Madhyamik Shiksha Abhiyan (RMSA); 4.7.6. Scheme 6: Navodaya Vidyalaya Samiti (NVS); 4.8. OUTPUT OF BUDGET ALLOCATION; CONCLUDING REMARKS. CONSENT FOR PUBLICATIONCONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES; APPENDIX A; ALLOCATION OCBA; Public Class Allocation_OCBA; Applet Window Code for Simulation; Simulation Pane Code for simulation; OCBA and EA Simulation Run; Optimal Computing Budget Allocation Simulation; Equal Allocation (EA) Simulation; Graph Generation; APPENDIX B; SIMULATION OF MEAN AND STANDARD DEVIATION; Calculation of Growth Rate; Department Wise Budget Allocation; Percentage Growth Rate Calculation; APPENDIX C; BUDGET ALLOCATION USING GENETIC ALGORITHM APPROACH FITNESS CALCULATION; GA Algorithm. GA Population Selection. Mathematical optimization. http://id.loc.gov/authorities/subjects/sh85082127 Optimisation mathématique. Mathematical optimization fast Khowas, Moumita. Sinha, Keshav. Print version: Sahana, Sudip Kumar. Budget Optimization and Allocation: an Evolutionary Computing Based Model. Sharjah : Bentham Science Publishers, ©2018 9781681087085 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1867478 Volltext |
| spellingShingle | Sahana, Sudip Kumar Budget Optimization and Allocation. Intro; CONTENTS; FOREWORD; PREFACE; DEDICATION; SUMMARY; Introduction; 1.1. IMPORTANCE AND CHALLENGES OF BUDGET ALLOCATION IN NATIONAL AND GLOBAL ECONOMY; Military; Health Care; Education; 1.2. ADVANTAGES AND DISADVANTAGES OF BUDGET ALLOCATION; 1.2.1. Benefits of Budget Allocation; 1.2.2. Disadvantage of Budget Allocation; CONCLUDING REMARKS; CONSENT FOR PUBLICATION; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES; Literature Review; 2.1. TRADITIONAL BUDGET ALLOCATION TECHNIQUE; 2.1.1. Rank and Selection Technique; 2.1.2. Incremental Budgeting Technique. 2.1.3. Zero-based Budgeting Technique2.1.4. Ordinary Least Squares Technique (OLST); 2.1.5. Two-stage Least Squares Technique (2SLST); 2.2. LINEAR OPTIMIZATION; 2.3. NONLINEAR OPTIMIZATION; 2.4. METAHEURISTIC OPTIMIZATION; 2.4.1. Pareto Efficiency or Pareto Optimality; Marginal Conditions of Pareto Optimality; Pareto Efficiency in Social welfare; 2.4.2. Optimal Computing Budget Allocation (OCBA); 2.4.3. Genetic Algorithm (GA); 2.5. LITERATURE SURVEY; 2.6. PROBLEM STATEMENT; CONCLUDING REMARKS; CONSENT FOR PUBLICATION; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES; Research Methodology. 3.1. BUDGET ALLOCATION SCHEME/MODEL3.2. BUDGET OPTIMIZATION TECHNIQUE; 3.2.1. Proposed Evolutionary Computing based Framework for Budget Allocation and Optimization; 3.2.1.1. Mathematical Finance; 3.2.1.2. Evolutionary Computing Approach; Pseudo code for the Crossover Process; 3.3. BUDGET ALLOCATION TECHNIQUE; CONCLUDING REMARKS; CONSENT FOR PUBLICATION; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES; Result and Discussion; 4.1. TEST CASE 1: GROWTH RATE CALCULATION; 4.2. TEST CASE 2: PERCENT GROWTH RATE; 4.3. TEST CASE 3: MEAN AND STANDARD DEVIATION TECHNIQUE. 4.4. OPTIMIZATION TECHNIQUE 1: OCBA TECHNIQUE4.5. OPTIMIZATION TECHNIQUE 2: EA TECHNIQUE; 4.6. OPTIMIZATION TECHNIQUE 3: GA OPTIMIZATION; 4.7. BUDGET ALLOCATION TECHNIQUE; 4.7.1. Scheme 1: National Council of Education Research and Training (NCERT); 4.7.2. Scheme 2: Kendriya Vidyalaya Sangathan (KVS); 4.7.3. Scheme 3: Central Tibetan School Society Administration; 4.7.4. Scheme 4: Scheme for Setting Up 6000 Model Schools; 4.7.5. Scheme 5: Rashtriya Madhyamik Shiksha Abhiyan (RMSA); 4.7.6. Scheme 6: Navodaya Vidyalaya Samiti (NVS); 4.8. OUTPUT OF BUDGET ALLOCATION; CONCLUDING REMARKS. CONSENT FOR PUBLICATIONCONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES; APPENDIX A; ALLOCATION OCBA; Public Class Allocation_OCBA; Applet Window Code for Simulation; Simulation Pane Code for simulation; OCBA and EA Simulation Run; Optimal Computing Budget Allocation Simulation; Equal Allocation (EA) Simulation; Graph Generation; APPENDIX B; SIMULATION OF MEAN AND STANDARD DEVIATION; Calculation of Growth Rate; Department Wise Budget Allocation; Percentage Growth Rate Calculation; APPENDIX C; BUDGET ALLOCATION USING GENETIC ALGORITHM APPROACH FITNESS CALCULATION; GA Algorithm. Mathematical optimization. http://id.loc.gov/authorities/subjects/sh85082127 Optimisation mathématique. Mathematical optimization fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85082127 |
| title | Budget Optimization and Allocation. |
| title_auth | Budget Optimization and Allocation. |
| title_exact_search | Budget Optimization and Allocation. |
| title_full | Budget Optimization and Allocation. |
| title_fullStr | Budget Optimization and Allocation. |
| title_full_unstemmed | Budget Optimization and Allocation. |
| title_short | Budget Optimization and Allocation. |
| title_sort | budget optimization and allocation |
| topic | Mathematical optimization. http://id.loc.gov/authorities/subjects/sh85082127 Optimisation mathématique. Mathematical optimization fast |
| topic_facet | Mathematical optimization. Optimisation mathématique. Mathematical optimization |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1867478 |
| work_keys_str_mv | AT sahanasudipkumar budgetoptimizationandallocation AT khowasmoumita budgetoptimizationandallocation AT sinhakeshav budgetoptimizationandallocation |