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180818s2018 xx o 000 0 eng d |
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|a 1048939421
|a 1264737783
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|a 1681087073
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|a 9781681087078
|q (electronic bk.)
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|a (OCoLC)1048920126
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|z (OCoLC)1264737783
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|a QA402.5
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|a HCDD
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|a Sahana, Sudip Kumar.
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|a Budget Optimization and Allocation.
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|a Sharjah :
|b Bentham Science Publishers,
|c 2018.
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| 300 |
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|a 1 online resource (164 pages)
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| 336 |
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|a text
|b txt
|2 rdacontent
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| 337 |
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a Print version record.
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|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.
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|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.
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|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.
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|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.
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|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.
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|a GA Population Selection.
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| 650 |
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0 |
|a Mathematical optimization.
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| 650 |
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7 |
|a Mathematical optimization
|2 fast
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| 700 |
1 |
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|a Khowas, Moumita.
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| 700 |
1 |
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|a Sinha, Keshav.
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| 776 |
0 |
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|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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| 856 |
4 |
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|u https://ebookcentral.proquest.com/lib/holycrosscollege-ebooks/detail.action?docID=5491305
|y Click for online access
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|a EBC-AC
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|a 92
|b HCD
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