We presented a parallel tabu search (PTS) algorithm for the traveling salesman problem (TSP), which is NP-hard. To parallelize tabu search (TS) algorithm efficiently, the search space decomposition based on partition principle was used to balance the computing load, while exploitation in subspace had been boosted by an adaptive search strategy of intensification and diversification. Numerical r...

We describe the use of a rewriting system to determine equivalence classes over the search-space of optimisation problems. These equivalence classes may be used to derive redundant subsequences in the search-space for incorporation into metaheuristics such as backtracking, genetic algorithms and tabu-search. We use this approach as the basis for a new tabu-search variant — ‘EquationalTS’ and ap...

This paper describes an attribute based tabu search heuristic for the Generalized Minimum Spanning Tree Problem (GMSTP) known to be NP-hard. Given a graph whose vertex set is partitioned into clusters, the GMSTP consists of designing a minimum cost tree spanning all clusters. An attribute based tabu search heuristic employing new neighborhoods is proposed. An extended set of TSPLIB test instanc...

We provide an improved algorithm called “a neighborhood expansion tabu search algorithm based on genetic factors” (NETS) to solve traveling salesman problem. The algorithm keeps the traditional tabu algorithm’s neighborhood, ensure the algorithm’s strong climbing ability and go to the local optimization. At the same time, introduce the genetic algorithm’s genetic factor (crossover factor and va...

Algorithms based on local search are popular for solving many optimization problems including the maximum satisfiability problem (MAXSAT). With regard to MAXSAT, the state of the art in performance for universal (i.e. non specialized solvers) seems to be variants of Simulated Annealing (SA) and MaxWalkSat (MWS), stochastic local search methods. Local search methods are conceptually simple, and ...

Tabu search has proven highly successful in solving hard combinatorial optimization problems. In this paper, we propose a hybrid method that combines adaptive memory, sparse dynamic programming, and reduction techniques to reduce and explore the search space. Our approach starts with a bi-partition of the variables, involving a small core problem, which never exceeds 15 variables, solved using ...

In this paper we present two generic parallel skeletons for Tabu Search method –a well known meta-heuristic for approximately solving combinatorial optimization problems. The first skeleton is based on independent runs while the second in the classical master-slave model. Our starting point is the design and implementation of a sequential skeleton that is used later as basis for the two paralle...

This paper presents an approach for the comparative cryptanalysis of Simple Data Encryption Standard (S-DES) using Tabu Search and Simulated Annealing methods. In this paper, cipher text only attack is adopted and varieties of optimum keys are generated based on the cost function values. The goal of this paper is three fold. First we want to make a study about how evolutionary computation techn...

This paper presents a highly effective memetic algorithm for the maximum diversity problem based on tabu search. The tabu search component uses a successive filter candidate list strategy and the solution combination component employs a combination operator based on identifying strongly determined and consistent variables. Computational experiments on three sets of 40 popular benchmark instance...

Tabu search (TS) algorithms are among the most efficient heuristic techniques in combinatorial optimization. Within these algorithms, it is important that the proper policies for maintaining the tabu tenure (tabu list size) are applied. In this paper, we discuss the mechanisms of defining the tabu tenure for the famous combinatorial optimization problem − the quadratic assignment problem (QAP)....