Data clustering is the process of partitioning a set of data objects into meaning clusters or groups. Due to the vast usage of clustering algorithms in many fields, a lot of research is still going on to find the best and efficient clustering algorithm. K-means is simple and easy to implement, but it suffers from initialization of cluster center and hence trapped in local optimum. In this paper...

Evolutionary Algorithms (EAs) are population based algorithms, which allow for simultaneous exploration of different parts in the Pareto optimal set. This paper presents Memetic Elitist Pareto Evolutionary Algorithm of Three-Term Backpropagation Network for Classification Problems. This memetic elitist Pareto evolutionary algorithm is called METBP and used to evolve Three-term Backpropagation (...

This paper introduces a hybrid genetic algorithm for the satisfiability problem (SAT). This algorithm, called GASAT, incorporates local search within the genetic framework. GASAT relays on a problem specific crossover operator to create new solutions, that are improved by a tabu search procedure. The performance of GASAT is assessed using a set of well-known benchmarks. Comparisons with state-o...

The 0-1 knapsack problem (KP) is widely studied in the last few decades. Despite of their simple structures, KP along with its extended versions belong to the class of NP-hard problems, and several optimization techniques have been developed to solve the problems. Some major examples are branch and bound methods and dynamic programming approaches [6], problemspecific heuristics [6], tabu search...

We present several heuristic algorithms based on tabu search for solving the multi-stage sequence-dependent group scheduling (SDGS) problem by considering minimization of makespan as the criterion. As the problem is recognized to be strongly NP-hard, several meta (tabu) search-based solution algorithms are developed to efficiently solve industry-size problem instances. Also, two different initi...

In previous work solutions for the nesting problem are produced using the no fit polygon (NFP), a new evaluation method and three evolutionary algorithms (simulated annealing (SA), tabu search (TS) and genetic algorithms (GA)). Tabu search has been shown to produce the best quality solutions for two problems. In this paper this work is developed. A relatively new type of search algorithm (ant a...

Thispaper presents a deterministic model, which takes into account the final water storage and the effects of water head, for optimal short term generation scheduling of a hydrothermal system. Considering its large scale mixed integer nonlinear structure, a hybrid algorithm based on Genetic Algorithm and tabu search is developed to solve it. The model is divided into thermal power dispatch and ...