The use of techniques for automating the generation of software test cases is very important as it can reduce the time and cost of this process. The latest methods for automatic generation of tests use metaheuristic search techniques, i.e. Genetic Algorithms and Simulated Annealing. There is a great deal of research into the use of Genetic Algorithms to obtain a specific coverage in software te...

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...

In this paper a new metaheuristic method is proposed to solve the classical permutation flowshop scheduling problem with the objective of minimizing sum of completion times. The representative neighbourhood combines the stochastic sampling method mainly used in Simulated Annealing and the best descent method elaborated in Tabu Search and integrates them naturally into a single method. The metho...

Many real life optimization problems are nonconvex and may have several local minima within their feasible region. Therefore, global search methods are needed. Metaheuristics are efficient global optimizers including a metastrategy that guides a heuristic search. Genetic algorithms, simulated annealing, tabu search and scatter search are the most well-know metaheuristics. In general, they do no...

A tabu search algorithm is proposed for the codebook generation in vector quantization. The key question is the definition of neighboring solution. Making random modifications to the current solution is not sufficient alone. The proposed algorithm first makes non-local changes to the codebook which is then fine-tuned by the generalized Lloyd algorithm (GLA). For a set of gray scale images, the ...

Given an undirected graph with costs associated both with its edges and unordered pairs of edges, the quadratic minimum spanning tree problem asks to find a spanning tree that minimizes the sum of costs of all edges and pairs of edges in the tree. We present multistart simulated annealing, hybrid genetic and iterated tabu search algorithms for solving this problem. We report on computational ex...