efficient operation of both primary and cognitive users. In this paper‚ an algorithm is used to dynamically control transmission power‚ which is capable of achieving reasonably good solutions fast enough in order to guarantee an acceptable level of performance for CU without degrading the performance of primary user(s). Genetic Algorithm is used to enhance the convergence time. Keywords: Cognitive radio‚ Genetic Algorithm‚ Power allocation‚ Quality of Service. I. INTRODUCTION The recent rapid
Premium Wireless Cognitive radio Radio
9 15 Draw a timeline for each of the following scheduling algorithm. (It may be helpful to first compute to first compute a start and finish time for each job). a. FCFS b. SJN c. SRT d. Round Robin (using a time quantum of 5‚ ignore context switching and natural wait) 6. Using the same information given for question 5‚ complete the chart by computing waiting time and turnaround time for each of the following scheduling algorithms (Ignoring context switching overhead). a. FCFS b. SJN c
Free Scheduling Scheduling algorithms Operating system
Complexities! Good Fair Poor Searching Algorithm Data Structure Time Complexity Depth First Search (DFS) Graph of |V| vertices and |E| edges Graph of |V| vertices and |E| edges Sorted array of n elements Array - O(|E| + |V|) O(|V|) - O(|E| + |V|) O(|V|) O(log(n)) O(log(n)) O(1) O(n) O(n) O(1) Graph with |V| vertices and |E| edges O((|V| + |E|) log |V|) O((|V| + |E|) log |V|) O(|V|) Graph with |V| vertices and |E| edges O(|V|^2) O(|V|^2) O(|V|) Graph with |V| vertices and
Premium
Vision Singapore‚ 7-10th December 2010 tinySLAM : a SLAM Algorithm in less than 200 lines C-Language Program Bruno STEUX - Oussama EL HAMZAOUI Robotics Center. Mines ParisTech Paris‚ FRANCE {bruno.steux‚oussama.el_hamzaoui}@mines-paristech.fr Abstract—This paper presents a Laser-SLAM algorithm which can be programmed in less than 200 lines C-language program. The first idea aimed to develop and implement a simple SLAM algorithm providing good performances without exceeding 200 lines in
Premium Robotics Algorithm
Modified Invasive Weed Optimization with Dual Mutation Technique for Dynamic Economic Dispatch * R. Sharma‚ Member‚ IEEE ‚ Niranjan Nayak‚ Member‚ IEEE ‚Krishnanand K. R. and P. K. Rout‚ Member‚ IEEE Abstract-- Dynamic economic dispatch (DED) is one of the main functions of power system operation and control. It determines the optimal operation of units with predicted load demands over a certain period of time with an objective to minimize total production cost while the system is operating
Premium Optimization Electricity generation Genetic algorithm
Executive Summary: Marketing Strategy Optimization: Using linear programming to establish an optimal marketing mixture. Drew M. Stapleton‚ Joe B. Hanna and Dan Markussen‚ American Business Review 2(21)-pg 54-62 June 2003 In recent times marketing strategy is playing a vital role in a firm success. It optimizes the marketing resources and can improve the revenue generation and market share. Since the global market place is increasing‚ companies find optimizing the marketing effort even more
Premium Marketing Optimization Operations research
Structures‚ Algorithm Analysis: Table of Contents 页码，1/1 Data Structures and Algorithm Analysis in C by Mark Allen Weiss PREFACE CHAPTER 1: INTRODUCTION CHAPTER 2: ALGORITHM ANALYSIS CHAPTER 3: LISTS‚ STACKS‚ AND QUEUES CHAPTER 4: TREES CHAPTER 5: HASHING CHAPTER 6: PRIORITY QUEUES (HEAPS) CHAPTER 7: SORTING CHAPTER 8: THE DISJOINT SET ADT CHAPTER 9: GRAPH ALGORITHMS CHAPTER 10: ALGORITHM DESIGN TECHNIQUES CHAPTER 11: AMORTIZED ANALYSIS mk:@MSITStore:K:\Data.Structures.and.Algorithm.Analysis
Premium Algorithm
1 A Modified Shuffled Frog Leaping Algorithm for Nonconvex Economic Dispatch Problem Eiman Sayedi‚ Malihe M. Farsangi‚ Mohammad Barati‚ and Kwang Y. Lee‚ Fellow‚ IEEE al. in [3]. To improve the performance of the SFL algorithm‚ a chaos search is combined with SFL by Li‚ et al. in [4]. In [5]‚ a new frog leaping rule is introduced and the direction and the length of each frog’s jump are extended by emulating frog’s perception and action uncertainties. Zhen‚ et al. in [6]‚ introduced a new leaping
Premium Optimization Genetic algorithm Frog
learning methods‚ and etc. In this project‚ genetic algorithm will be used to solve this problem by using GAlib package. Genetic Algorithms are adaptive methods which may be used to solve search and optimization problems. They are based on the genetic processes of biological organisms. Over many generations‚ natural populations evolve according to the principles of natural selection and "survival of the fittest". By mimicking this process‚ genetic algorithms are able to "evolve" solutions to real world
Premium Genetic algorithm
iust.ac.ir/ An Iterated Greedy Algorithm for Solving the Blocking Flow Shop Scheduling Problem with Total Flow Time Criteria D. Khorasanian & G. Moslehi* Danial Khorasanian is an M.S. Student of Department of Industrial Engineering‚ Isfahan University of Technology‚ Isfahan‚ Iran Ghasem Moslehi is a Professor of Department of Industrial Engineering‚ Isfahan University of Technology‚ Isfahan‚ Iran KEYWORDS Constructive heuristic‚ Iterated greedy algorithm‚ Blocking flow shop‚ Total flow time
Premium Algorithm