Tabu

Casertaa and Uribe [46] proposed a Tabu Search (TS) based memory-mechanism for problem solving. It was capable of navigating both local information and in-formation from search space. They took tabu tenure as the performance measuring metrics. The efficiency of this algorithm was verified by testing four benchmark problems using problem solving software. The results showed that TS produced globally optimal solution in CPU time less than 0.1 seconds. Further they have generated large random instances

Culture is not just about race, family background, and inheritance. It is bigger than that. Characters and actor’s choice are significant to present this. Characters used in the book and movie relates. When I was reading the book, I had an idea of how Ashima, Gogol, Ashoke looks. Most of those ideas were true. I thought Gogol would be better looking and darker shade skin. Ashima is exactly what I thought she would look like. Ashoke is shown as this perfect husband, dad a provider. A lot of Gogol’s

The value to be used for updating the estimated value has been chosen as 181 (the value of range of each subgroup) for the first iteration of the algorithm. The value of an intermediate data has been taken as the range of each subgroup/ number of subgroup (181/6 = 30.16). That intermediate value 30.16 has been chosen as a change in temperature for the second iteration of algorithm. For third iteration, the value (30.16/6) 5.02 has been considered as a change in temperature. Similarly for the next

computation techniques. The mode of origin is another basis to distinguish between nature inspired and no nature inspired metaheuristic algorithm. Evolutionary computation and Ant Colony Optimization belongs to the class of nature inspired whereas tabu search and iterated local search belongs to the class of non nature inspired algorithms. Metaheuristic algorithms are also known as search based techniques or optimization algorithms which when applied to software engineering problems gave rise to

Now-a-days optimization and testing in software engineering using traditional techniques has become a tedious task. In order to fasten this process, search based-software engineering (SBSE) techniques are introduced to solve real world large scale problems efficiently. SBSE techniques consisting of several algorithms can be implemented throughout the software development life cycle in order to deliver a more reliable product. This paper reviews the application of five major SBSE methods and the issues

As traffic increases and links become congested, people may suffer delays and long travel time for their daily trips. Planners may decide to improve this situation for people in the area. One of the options for improving the conditions of traveling in the congested area is link expansion. Link expansion projects in transportation networks are almost always interdependent. When capacity of one link in a network changes it affects the flow of other links, and may shift bottle necks elsewhere throughout

utilized to search for the new unknown area of the searching space.Its show eective use of historic information that makes every search moving forward according to the best direction, genetic algorithm is similar to simulated annealing algorithm and tabu searching [9]. As a result, genetic algorithm is not only a random searching approach, but also a directing random searching approach. In this paper, we use Genetic Algorithm(GA), called Genetic Algorithm 2 for Attribute Reduction (GAAR), to solve

MANET-“ A mobile ad-hoc network is a self-configuring infrastructure less network of mobile devices connected by wireless.”. Each device in a MANET is free to move independently in any direction, and will therefore change its links to other devices frequently. Each must forward traffic unrelated to its own use, and therefore be a router. The primary challenge in building a MANET is equipping each device to continuously maintain the information required to properly route traffic. A routing protocol

Advertisement: Greek Statue and Perfume While flipping through the pages of a fashion magazine, my fingers stop abruptly as my eyes catch an image of a nude man holding a clothed woman. The man has a muscular body and is effortlessly supporting the woman who's body is arched backwards, her arms hang in a swan-like manner. On the ground by her left foot lays a paint palette and her right hand is grasping a paint brush. The room that they are in appears to be a studio with press board floors,

Job shop schedsuling using genetic algorithm Abstract—The job-shop scheduling (JSS) can be difined as a planning of schedules with many variations according to the requirements. In job-shop scheduling problem (JSSP) environment, there are numbers jobs to be processed on numbers of machines with a certain objective function to be minimized or maximized. In this paper, we have used the GT-GA to solve the job shop scheduling to minimize the makespan along with the special type of crossover