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positions will cause the swarm never to reach an equilibrium state While not all the methods discussed below consider this fact, all of the methods can address the problem by reducing the amount of chaos over time Kennedy and Eberhart [449] were the rst to mention the advantages of randomly reinitializing particles, a process referred to as craziness Although Kennedy mentioned the potential advantages of a craziness operator, no evaluation of such operators was given Since then, a number of researchers have proposed di erent approaches to implement a craziness operator for PSO When considering any method to add randomness to the swarm, a number of aspects need to be considered, including what should be randomized, when should randomization occur, how should it be done, and which members of the swarm will be a ected Additionally, thought should be given to what should be done with personal best positions of a ected particles These aspects are discussed next The diversity of the swarm can be increased by randomly initializing position vectors [534, 535, 863, 874, 875, 922, 923] and/or velocity vectors [765, 766, 922, 923, 924] By initializing positions, particles are physically relocated to a di erent, random position in the search space If velocity vectors are randomized and positions kept constant, particles retain their memory of their current and previous best solutions, but are forced to search in di erent random directions If a better solution is not found due to random initialization of the velocity vector of a particle, the particle will again be attracted towards its personal best position If position vectors are initialized, thought should be given to what should be done with personal best positions and velocity vectors Total reinitialization will have a particle s personal best also initialized to the new random position [534, 535, 923] This e ectively removes the particle s memory and prevents the particle from moving back towards its previously found best position (depending on when the global best position is updated) At the rst iteration after reinitialization the new particle is attracted only towards the previous global best position of the swarm Alternatively, reinitialized particles may retain their memory of previous best positions It should be noted that the latter may have less diversity than removing particle memories, since particles are immediately moving back towards their previous personal best positions It may, of course, happen that a new personal best position is found en route When positions are reinitialized, velocities are usually initialized to zero, to have a zero momentum at the rst iteration after reinitialization Alternatively, velocities can be initialized to small random values [923] Venter and Sobieszczanski-Sobieski [874, 875] initialize velocities to the cognitive component before reinitialization This ensures a momentum back towards the personal best position The ext important question to consider is when to reinitialize If reinitialization happens too soon, the a ected particles may not have had su cient time to explore their current regions before being relocated If the time to reinitialization is too long, it may happen that all particles have already converged This is not really a problem, other than wasted computational time since no improvements are seen in this state Several approaches have been identi ed to decide when to reinitialize:.

Component One of a set of values used to represent a pixel in a particular color model Most color models represent a color value using three component values CRC Cyclical Redundancy Check A polynomial-based method for detecting corrupted data Data Unit In JPEG, an 8 8 block of sample values for a single component DC Coefficient The lowest-order DCT coefficient It represents a constant value DCT Discrete Cosine Transform A mathematical process that converts a set of values into an equivalent representation as the sum of cosine functions Deflate The compression process used in PNG It is a variant of the LZ77 process that incorporates Huffman coding Down-Sampling The process of reducing the resolution of a component in an image Frame In JPEG, a group of one or more scans For the JPEG modes in common use a frame is indistinguishable from an image Gamut The range of colors that can be displayed on a particular output device Gamma A model commonly used to correct colors in an image based upon the properties of the system and the viewing environment Hierarchical JPEG A little used JPEG mode where the image is broken into a number of frames that refine the image Huffman Coding A compression technique that uses variable-length codes to epresent data Inflate The decompression process used in PNG It is the reverse of the Deflate process Interleaved Scan In JPEG, a scan that consists of more than one component. In Visual Studio .NET Using Barcode encoder for .Related: Code 128 Generation .NET , Word Intelligent Mail Generation , UPC-E Generator Java

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Page 31 project development to the larger issue of the strategic use of projects as a method to gain competitive advantage in the marketplace Quality chain thinking requires companies to think in terms of how and where they can best offer value o their potential customer base This operating philosophy is beneficial because it starts shaping and refining our thinking in terms of what we do best What types of contracts should we be competing for What geographical or regional areas are we most capable of supporting What types of projects can we derive the greatest profit margins from, relative to our competition These are some of the questions that naturally follow from an understanding of project management within the quality chain Customer-based ideas for project management are new and require companies to think outside traditional approaches That offers readers either intense discomfort or highlights entirely new levels of possibility: There is very little middle ground here The good news is that these ideas have been proven to work, they are not just the result of sterile theoretical thinking Several organizations we have either worked for or consulted with have put these approaches into practice with highly successful results for them and their customers That is the key point: What is being offered here is win-win project management Not profit at the expense of the customer but mutual opportunity and payoff for all parties to the process It is our belief that implementing these ideas will lead many tradition-bound project organizations to looking at projects in an entirely different light In this new model, we can chart an approach that makes the customer an equal partner in the process.

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